Location Management Proposals:

Survey and Evaluation

by

Atif Aluim Siddiqi, B.Se. Eng.

University of E n g i n h g & Technology, Lahore, Pakistan

A thesis subrnittecî to

the Facuity of Graduate Studies and Research

in the partial Milment of

the requirement for degree of

MSc. in Ioformatioa and Systems Science

Department of Systems and Computer Engineering

Carleton University

1 125 Colonel By Drive

Ottawa, Ontario, K 1 S SB6

Canada.

Apni 1,1999

(B Copyright 1999, Atif Aham Sibiiqi

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Abstract

The challenge of supporthg rapidly gmwing numbers of mobile users, wMe coilstrained

by limiteci radio spectruni is being fâced by cellular network operators worldwide. The

standard technique for cellular networks is to decreax radio ce11 size, thereby rnaintaining

a supportable subscriber density. However, smaller size d t in i n d signalhg for

location management procedures, which reduces the bandwidth available for user traffic.

S e v d location management schemes have b e n proposed to improve the performance

of such networks, but a fair assessrnent and comparison of their performance is diacuit

without a realistic mobility d e i , since the performance of location management

schemes depends considerably on subscriber mobility patterns. Some of the methods used

in the Literahue are reviewed and comented upon. The strategies are then classified in

several categories on the basis of theïr hctioIliility. Finally, some proposais are selected

that concentrate on the location updating and paging overhead.

To analyze the performance of the selected ptoposals, two mobility models were used in

this thesis. The fïrst was a realistic, measurement-based, place and tirnedependent

individual mobility model to simulate the mobility behavior of actual people. The second

was a random mobility mode1 based on simplifieci assumption, such as a unifonn

distribution of the direction of travel for each mobile subscriber, as being used in a

number of proposed schemes.

From the results it is clear that the mobility model bas a signifiant impact and the results

described in various schemes using a random mobility mode1 may not reflect the relative

performance when deploying schemes in actuai systems.

iii

Acknowledgements

1 would Iüre to express my sincere îhanùs to my thesis supervisor, Dr. Thomas Kum, for

his invaluable guidance and helpnil suggestions during the course of this thesis. This

thesis would not have been possible but for his enthusiasm for research and his

rmarkable reviewing speed-

1 would like to thank all the d e n t s of tht Bmadband Network Lab for puthg up the

nice working atmosphere and the staff of the Department of Systems and Cornputer

Engineering for theis help in the development of this thesis.

1 would iike to thak my ~ t s and brothers for their prayers and support,

encouragement and guidance throughout my acadernic pursuits.

Last, but wt the least, I would WEe to thank my wife who provided me with a continuous

source of inspiration and for her patience and strong support without which the research

would not have been possible.

Table of Contents

ACCEPTANCE SEEET ............................................................... II

.................................. ~STRACT.....o.....oœœ.m.œ..m..............m.om........m œœ..œ.UI

ACKNOWLEDGEMENTS ...~............................................................. IV

TABLE OF CONTENTS ......................................................................... V

LIST OF TABLES ......wmœ..~..œœ..œ.œmU.m.wœU...œ.e...o.œHom,~..œ..~.oo..... .. VU LIST OF FIGURES ....................................................................... \1II

LIST OF ACRONYMS .................................................................................. X

3.1 -1 : 1 Variations in Implementing Location Areas ............... ... ........ 29

v

INTRODUCTION ........ .....-..œœ..H.H1.. wœœœœ ......... .. ................ 1

............................................. Generai Concepts in Location Management 1

.................................................................................... Problem Definition 4

................................................................................................. Motivation 5

............................................................ Basic Proposal and Thesis Outline 7

LOCATION MANAGEMENT PROCEDURES ......... .œœœ.mH.œ .m.....m...... 9

GSM L d o n Management Fundamentals .............................................. 9

The Architecture of GSM Netwock ........................................................ 9 Location Management Proceduces in GSM ................... ,.., ........... 13

IS-4 1 L d o n Management Fundarnentals ..... ..... .. .. .......................... 23

...................................................................... C~nclusions .................. ..... 24

PREVIOUS WORK ON LOCATION MANAGEMENT

PROPOSALS WITZ5 CLASSIFICATION au--- ..w.oo*.œœ a-œmeœo.*.œ. 26

Classification of Location Management Strategies ................................. 27

Location Updating and Paging Reposais ......................................... ... 27

3.1.1.2 LocationUpdatingwithAltcrnativeTriggas ................................... 3 8

3.1 2 Interrogation-Basai Proposais ........................................................... 4 0

3 . 2 1 Disbn'butedDatabaseArchitecnue ..................................................... 42

3.1.2.2 Hybrid Database Architecture ........................................................... 46

CHAPTER 4

CHAPTER 5

CHAPTER 6

Proposais Evduation ......................... ...................... . 54

Conclusions ............................................................................................. 72

MOBILITY MODELS AND EXPERIMENTAL SETUP ................ 77

Realistic Mobiiity Mode1 ........................................................................ 79

Random Mobility Mode1 .,... ......... .......,. ....................................... 80

Simulation Procedure .............................................................................. 81

Goals and Constraints of the Algorithms ............................................. 82

Siunmaiey ................................................................................................. 89

PERFORMANCE ANALYSIS ~ . ~ œ ~ . o O O ~ O O ~ ~ O O . m ~ ~ œ O H . H O ......................... 91

Description of Data and Procedures ....................,................ ...-.......... 92

Cornparison of Location Management-Related Signaling ...................... 93

OveraU Average Performance .............................................................. 93

Total Location Management Cost ..................................................... 102

CONCLUSIONS AND FUTURE WORK .. ..O.-.HI.H..H..OO~.OH.."* ..... 1 15

Conclusions .....................................................~..................................... 115 Future Work .................................. ..., .................................................. 116

List of Tables Table 5.1 : 99.h Confidence Intervai Estimation of Location Updates under the

Reaüstic Mobiiity Model ....................................................... ..................... . 95

Table 5.2: 99.h Confidence Intewai Estimation ofLocation Updates under the

Random Mo bility Model . ......... - . .. -. . .. .. . -. .. .... . .. .. .. . . .... . . . . - -. .. . . .. . . -. ..-...... . .. . . . . 9 7

Table 5.3 : 95% Confidence Interval Estimation of Number of Cells Paged for 6

Incomhg Caiis under the Realistic Mobility Model ...... .... ,. .... .. . .. ...... .. .. . . .. . . . 1 0 1

Table 5.4: 99% Confidence Intervai Estimation of Nimber of Ce& Paged for 12

Incomïng Catls under the ReaJistic Mobility Model ..,-.--.,......-.......tY....tY...tYtY.... 1 O I

Table 5.5: 99% Confidence Interval Estimation of Number of Cells Paged for 6

Incoming Calls under the Random Mobility Model ..,....................... ... .. . . . . .. . 1 02

Table 5.6: 99% Confidence Interval Estimation of Number of Cds Paged for 12

Incoming Calls under the Random Mobility Model .........-.............. ....... 102

Table 5.7: 99% Confidence Interval Estimation of Total Location Management Cost

for c = 5 and 6 1ncomi.g Calls under the Realistic Mobiüty Model ............. 107

Table 5.8: 99% Codidence interval Estimation of Total Location Management Cost

for c = 5 and 12 Incoming Calls under the Realistic Mobility Model ........... 1 O7

Table 5.9: 99% Confidence Interval Estimation of Totd Location Management Cost

for c = 10 and 6 Incorning Cails under the Realistic Mobility Model ........... 1 O8

Table 5.10: 99% Confidence Interval Estimation of Total Location Management Cost

for c = 10 and 12 Incoming Cails under the Realistic Mobility Model ...... 108

Table 5.1 1 : 99% Confidence laterval Estimation of Total Location Management Cost

for c = 5 and 6 Incoming Calls under the Raadom Mobiiity Model ............ 113

Table 5.12: 9% Confidence latemal Estimation of Total Location Management Cost

for c = 5 and 12 Incoming Calls under the Random Mobility Model .......... 1 13

Table 5.13: 99?4 Confidence intemal Estimation of Total Location Management Cost

for c = 10 and 6 Incoming Calls under the Random Mobiiity Made1 .......... 1 14

Table 5.14: 99% Confidence Inte~al Estimation of Total Location Management Cost

for c = 1 O and 12 Incoming Cails under the Random Mobility Model . ....... 1 14

vii

List of Figures

Figure 2.1. Architecture of a GSM NctworSc ................................................................... 10

............................................. Figure 2.2. Message Exchange for GSM Location Updates 15

Figure 2.3 : Message Exchange for GSM Intemgation and Paging ................................. 21

Figure 3.1 : ClassXcation of Location Management Roposals ........................................ 28

Figure 4.1: Total Location Management Cost under the Realistic Mobility Model for

Z = 3747Sy6t7 ... ............................o~....~~.....r....o.....................~............... ... 84

Figure 4.2: Total Location Management Cost under the Randorn Mobility Model for

2 = 1,2,3.4.5.6, 7 ............................................................................................. 86

Figure 4.3: Total Location Management Cost under the Realistic Mobility Model for

T = 1,2,3,4,5,6, 7 ............................................................................................. 88

Figure 4.4: Total Location Management Cost under the Random Mobiiity Model for

T = 1,2,3,4.5,6, 7 ............................................................................................. 89

Figure 5.1 : Global Average Number of Location Updates versus Elapsed Time under

the Realistic Mobiity Mode1 ................... ... ...........O........................... 9 4

Figure 5.2: Global Average Number of Location Updates vemis Elapsed Time under

the Random Mobility Mode1 ................................................................... 9 6

Figure 5.3: Global Average Number of Cells Paged for 6 Inwming Calls versus

Elapsed Time under the Realistic Mobility Mode1 ....................................... 98

Figure 5-4: Global Average Number of Ceiis Paged for 12 hcoming Calls versus

Elapsed Time under the Realistic Mobility Mode1 ........................................ 98

Figure 5.5: Global Average Number of Ce& Pa@ for 6 Incoming Calk versus

Elapsed T i e mder the Ibndom Mobility Mode1 ..................................... 9 9

Figure 5.6: Global Average Number of CeUs Pageà for 12 Incominp Calls versus

Elapsed T i e under tbe Random Mobility Mode1 .............. .... .............. 100

Figure 5.7: Global Total Location Management Cost (c = 5) for 6 Incoming Calls

versus Ehpsed T h e Mder the M o b i i Mode1 ........................... 104 Figure 5.8: Global Total Location Management Cost (c = 5) for 12 Incominp Calls

vctsus Elapsed Thne imda the Redistic M o b ' ï Mode1 ................... ..... 105

viü

Figure 5.9: Global Total Location Management Cost (c=lO) for 6 Iacoming Calls

versus Elapsed T'me under the Realistic Mobility Mode1 ........................... 106

Figure 5.10: Globd Total Locaiion Management Cost (c = 10) for 12 Incominp Calls

versus Elapsed Time under the R-c Mobility Mode1 ......................... 1 06

Figure 5.1 1 : Global Total Location Management Cost (c = 5) for 6 Incoming Calls

versus Elapsed Time under the Random Mobility Mode1 ........... ...- .... 109

Figure 5.12: Global Total Location Management Cost (c = 5) for 12 Incoming Calls

versus Elapsed Time under the Randorn Mobility Mode1 .......................... 1 10

Figure 5.13: Global Total Location Management Cost (c = 10) for 6 Incoming Calls

versus Elapsed T h e under the Radom Mobiiity Mode1 .......................... 1 1 I

Figure 5.14: Global Total Location Management Cost (c = 10) for 12 Incoming Caiis

versus Elapsed Tiie undtr the Radom Mobilïty Mode1 .............. ,,. ..... 1 12

List of Acronyms

PCS

MT

HLR

VLR

BS

BTS

RAILA

PA

MSC

LU

PSTN

PFSHLR

PFDHLR

OSPFDHLR

GPC

MAP

TLA

LMTs

LCMR

HOPPER

HIPER

DR

STP

RDB

HDB

TGMTS

PHs

PACS

Personal Communication Services

Mobie Terminal

Home Location Register

Visitor Location Register

Base Station

Base Transceiver Station

Registration Area in 1s-41/ Location Area in GSM

Paging Area

Mobile Switcbiag Center

Lacation Update

Public Switching Telephone Network

Pointer Fomarding with Single HLR

Pointer Forwarding with Distributed HLR

One-Step Pointer Forwarding with Distributed HLR

Global Personal Communication

Mobile Application Part

Two-Location Algorithm

Location Management Techniques

Locai Cail to Mobility Ratio

Hierarchical Online Parametric ProfilE Replication

Hierarchical P d l E Repl idon

Directory Registers

Signal Transfer Point

Regional DataBase

Home DataBase

Third Generation Mobile Telec0111113unication Systems

Pasonai Handyphoae System

Personal Access Communication System

Chapter 1

Introduction

1.1 Generd Concegrs in Locaiion Management

In the past few years, &et demand bas gmwn rapidIy for Personai Communication

Services (PCSs) such as digital cellular mobile radio systems, the Peisonal Access

Communication System (PACs), and the Japanese Personal Handyphone System (PHs).

This can be attribua to several factors, including decreasiag prias, impmved radio

coverage, and compact lightweight terminais. These second-generation wireless

communication systems are designad for particuiar applications and envùonments.

Customer demand for these systems has i n d dramatically every year. In Japan, for

example, the subscriber growth rates h m September 1995 to September 19% have nsen

by 129% for digital cellular mobile radio systems (PDC) and 288% for PHS [23]. in

gened, as the numkr of subscribers increases given a fixed radio spectrum allocation,

the size of raâio average cells must deaease, in order to accommodate the higher

subscriber densities. This mates many challenges, especially concenllng location

management. PCS, which are higher-capacity and lower-power cellular networks with

smder cells, face simiiar location management issues.

Compareci to second-generation systems and apart nom the increased traac demands, the

employment of location management and handoff procedures in a microcellular

environment, in conjuncton with the huge number of Location Updates (Lus), wiil

generate a considerable "mobility-related signaling" load. The increase of mobility-

related signaling apart nom the radio liak wiil have a major impact on the number of

database transactions, thus causing the database to be a possible bottleneck at the h e d

network side. Consequently, given the scarcity of radio mornes, methods for s i m g

load reduction are emerging for Thkd Generation Mobile Telecommunication Systems

(TGMTS). it is obvious that optimization techniques and enicient network planning

algorithms are criticai issues conceming overall TGMTS performance.

Location management is concemed with the procedures required to enable the netwodc to

maintain location information for each subscriber, or more specificaily, for each active

mobile terminai with a registered subscnkr, and to efficienuy hande the establishment

of incoming calls.

The location management procedures are required in cellular networks to manage

subscriber mobility. In general, mobiity management can k divideci into three different

aspects: temiinal, service and personal mobility, with the latter king the goal of modern

cellular systems. Temiiaal mobility is a network capability that enables mobile tenmioals

to access telecommunication services fiom any location, while in motion, and the

capabi1ity of the network to Locate and ideni& a mobile terminai as it m e s . In contrast,

personal mobility allows customers to access the network, independent of the location

and type of terminal that a customer happens to use at a given tirne. This is accomplished

by allocathg an identity numba not only to the terminal, but also to the subscriber, and

keephg an association between the subsaiber and the terminal. In practice, this invo1ves

the use of a personaiized smaa card which can be iasated into any compatible tcmiinal,

and which allows calls to be made and received at that partidar terminal, witb proper

billing and c d routing. Service mobility enables customers to access the same type of

network services, regdess of their cunent locations and tenninals in use, as if the

customers were at home or office.

The two hdamental procedures that comprise the basis of location management are

location updaîhg and paging. For the network to route incornhg calls to a mobile user,

each mobile user is requirtd to report its Location to the network at specinc points in tirne.

This reporting is known as Location Update (LU). Tecminal paging is the pmcess of

contacthg a specïfied user at its current address. Paging messages are broadcast in one or

more paging areas, contained within the cumnt location area, and idorm the target user

of the incomiog call. These concepts will be defined in more detail below.

The smaliest unit of location information that cellular networks are concemed about is a

radio cell. A ceii is the geographical area over which the average si@ strength h m the

radio transmitter that defines the cell is over some tbreshold, as compared to neighbo~g

cek and fkquencies. Cens are ideally represented as hexagons, aithough in reality,

interference and paîh losses due to irregular tmain and neigbboring cells, as weii as

power controf algonthms, smear cell boundaries into fuzzy, irregular shapes.

With the conventionai location management strategies, the network coverage m a is

divided into srnalier ce11 clusters caifd Location Areas (LAS) and Paging Areas (PAS).

LA is the granularity at which the nenvork keeps track of the location of the Mobile

Terminal (MT), Le., LA is that group of ceUs in which the MT must be located (provided

that the system is WU-fûnctioning and the M ï is powered-on). PA is the set of celis over

which a paging message is sent to Wonn the subscri'ber of an incornhg cali. Ln most

operational systems, LA and PA are identicai. For this teason, any grouping of cells for

location management purposes is usually caiied a LA.

The relationship between location updates, paging, location areas, and paging areas can

best be illustrateci by the two e-e approaches to location management. The f k t

approach is known as the Always-Updatt, in which each mobile user aansmits an update

message whenever it moves into a new ceil, and the Never-Update, in which the users

never send update messages regarding theù l d o n . Clearly, imder the former sttategy

the overhead due to transmissions of upda!e messages is very high, especidly in networks

with small ceils and a large number of highly mobiie users, but the overhead of finding

users is zero since the curent location of each user is always known. With the latter

stmtegy there is no overhead for updffting but whenever there is a need to fhd a particular

user, a network-wide search is quired, and this overhead is very high.

Personal communication Service provides seamiess and uninterrupted communication to

mobile subscribers. PCS users carrying M T s can communicate with a reaiote texminai

(mobile or static) regardless o f its cumnt location and mobility pattern. However, unlike

static networks, such as the intemet, where muting information is embedded in the

address of each node on the network, the c u m t location of a MT c a ~ o t be obtained

fiom its identification numberber A location management scheme, therefore, is necessary to

effectively keep tracfc of the MT'S a d to locate a d e d MT when a cal1 is initiated.

Consider the problem of routing a cail to a mobile unit M. A muest for a connection ta

M is generated fiom some point P in the nehuork. Since mobile units change locations, a

physical address must be found. The means by which the network obtains infiormation

about unit location is through some combination of paging (issuing polling signais in

likely locations) and registration (the unit identifjing its location). A fair amount of

previous work develops paging and registration procedures that mlliimize some cost

hction ( u d y signahg over the wireless andlor fixed network) for simple mobility

models or specinc systems.

Another body of work addresses the problem of how to optimdly store and update

location information throughout the network. Specificaiiy, network resources at point P

must have some knowledge of how to route a cal1 to unit M. A number of possibilities

exist. For example, should there be a centrai databasey which contains the exact location

of every mobile termioal, should every location have its own copy of the database, or

should locations have partial information? if so, how should it be ordered and updated?

Thus one body of literature opthizes location Somation gathering (paging and

registration); whereas the other assumes terminal locations arp known and optimiZe

dis Semination of Location uifonaation over the network. Both, however, make

assumptions about the trrmioal mobility eitber through the use of simple mobility models

or by more general intuitive notions such as Iocality of movement.

As desdbed in Chapter 2, location management as currendy perfôrmed is suitable for a

relatively small number of subs~ribers~ in a cellular environment that uses relatively large

cells. The definition of location areas, which uui obviously greatiy influence the location

updating and psging trsffic, is performed staticaily, using aggregte statistics and traflic

patterns- While the overail number of subscribers is relatively low, and the location areas

are moderately large, the signaling M c volume remains acceptable-

One of the important issues in cellular ~ t w o k s is the design and analysis of strategies

for tracking the mobile users. In these networks, whenever tiiere is a need to establish

communication with aay particular user, the network has £bt to find out which base

station can communicate with that user- This is due to the fact that the users are mobile

and codd be anywhere within the atea wvered by the network.

In recent years, many sophisticated location management schemes 11-27 have been

proposed to reduce profile lookup and update response t h e s and sigaaling tratnc. These

methods ufilize techniques such as data replication, caching, pointer fowarding and

hierrachicai database schemes. Review of several papers is given in chapter 3. It is

important to note that the actual @ormance of tbese proposais depends strongly upon

user behavior. For example, the merits of caching and data replication schemes are

fûnctions of user mobility and calling patterns. Furthemore, different schemes optimize

their pe&omance to different aspects of user behavior. As a mult, accurate user behavior

models are required when evaluating the performance of location management schemes.

The motivation behind this thesis is the realiPltion that in order to quantitatively and

realistically assess any location management scheme, an accuTate and plausible mobility

model must be used. A mobility model is an adytical or statistical representation of the

daily movements of mobile subscn'bers. In cellular mobile communication networks the

number of users aiiocated to a particular base station is a andom variable due to the

mobile nature of the users. This inherent fkature affects the behavior of the system in

terms of the offered td f ic - So, the iafluence of the mobility and trafnc of users must be

studied,

I.4 Basic Propasal and Thesis Outhe

As users become accustomed to wireless comm~cations, they expect to be reachable

anywhere' anytime, and in any communication medium. This places a burden on the fïxed

network to keep track of the user's locations to provide seamiess communications as

users move fmm o w place to another. A number of location management schemes have

been proposed in order to impmve upon the performance of existuig location

management algorithms, especially in second-and-third-generation cellular systems.

Some are! nlatively easy to Unplement, sow might provide high sigaaling savings on the

radio lhk, and some seem to be interesthg h m a theoreticdconceptual point of view-

The first contribution of this thesis is the detailed survey of some of the recent location

management proposais. The second contribution is the use two mobility models to

compare the performance of dinerent location management algorithms and showing the

impact of the mobility mode1 on the relative performance of these schemes.

Chapter 2 discusses the procedures involved in location management, both in general

terms and as implemented in the GSM cellular network standard and a brief review of IS-

41 standard In chapter 3, previous wodc on location management is reviewed by

arranging different proposah in dinetent categones. The advantages and disadvantages of

various approachcs are d i s c d Furthemore several algorithms wiii be selected

amongst these proposais for fiiahr evafuation wing two mobility m d s : a rraüstic

mobility mode1 and a random mobility model.

The mobility models that fomied the basis of the simulation study are describeci in

Chapter 4. A description of selected aîgorithms and their implementation under both

mobiiity models is also described in this chapter. In Chapter 5, the results h m the

simulation study are presented and analyzed. Conclusions fiom the simuiation and

possible futinc wolk are discussed in Chapter 6.

Chapter 2

Location Management Procedures

2.1 GSM Location Management Fundamenfafs

GSM is the second generation Pan Europcan Digitai cellular standard that has rapidly

gained market share worldwide since its debut in 1991. It has been chosen to provide

PCS in Europe, partly because widespcead roaming is a key requirement in PCS. Unlike

d o g fht-generation systems such as AMPS (Advanced Mobile Phone Services) used

in the United States GSM tranSniits digital signais over the radio interface as well as

internally between different network elements. It provides ISDN compatibility in terms of

user sewïces offered and general protocol structure, altbough not in terms of data rates,

since the allocated radio spectnim is Limite&

The location management concepts and procedures will be expiaincd in greater detail by

lookuig at their impiementation in the GSM digital cellular standard. For many location

management proposais, a scheme similar to the one used in GSM is used as the standard

of cornparison-

2. I . 1 The Architecfure of GSM Ne~work

The fimctional architecture of a GSM network c m be divided into two levels: the

stationary and mobile level. The stationary level comprises of the base station subsystem

and the network switching system while the mobile level consists of mobile terminais, as

r

BSC BSC BSC BSC

BTS BTS BTS BTS BTS BTS BTS BTS

Figure 2. 1: Architecture of u GSM Network

shown in Figure 2.1. Each subsystcm is comprisexi of hctional entities that

commUILicate through various interfaces using specified protocols.

Mobile tevel:

Mobile level consists of Mobile Terminais that communicate with base stations via

wireless links. Mobile tenninals are either vehicle-mounted or hand-held terininais used

by subscribers to send a d receive information- The GSM mobile terminai consists of two

entities: the mobiie equipment itself and a smart card called the Subscriber Identity

Module (SI . ) - The SIM card is an integrai part of the GSM design, which allows the

implementaîion of personai mobility. A subscriber cm plug the SIM card into any GSM

terminai and is able to place and receive d i s , with proper routing and billing.

Base Sfotron Subsvsrcm=

The Base Station Subsystem is composed of two parts, the Base Transceiver Station

(BTS) and the Base Station ConWer @SC) and handes almost al1 radio resource

aspects of GSM. The Base Transceiver Station houses the radio transceivers that define a

ceil and it also bandles the radio-Iink pmtocols with the MT. A BTS is assigned a set of

fkequencies in such a way that interference h m other ceiis in the network reusing the

same fiequencies is kept to a minimum, while maintaining enough radio channels in a

celi to handle the required subscriber density. The Base Station Controiier manages the

radio resources for one or more BTS. It handles setup and release of radio c h e l s ,

kquency hopping, and inter BTS handoff.

Mobile Swiîching Cemter:

At the stationary level, the Mobile Switching Center (MSC) is a central office, wbich

provides the d l processing and chawel setup hctiodity. The MSC interconnects

Mobile Tenninals (MTs) with other Mïs through Base Stations (BSs) or interoperates

with other MSCs and public k e d networks. The hctionality of the MSC is provided in

conjunction with the following databases de- in the GSM architecture, which together

with the MSC fom the Netwodc Switching Subsystem:

Home Location Register (HLR)

Visitor Location Register (VLR)

The MSC and the databases communicate using the Mobile Application Part (MAP)

protocol, which uses the SeTvices of Signahg System No. 7 (SS7) that is used as a

transport mechanism for cal1 control and database transactions.

Horne Locatioa Rcgistcr:

The Home Location register @LR) in GSM contains the pemument subscriber

parameters n r h as the type o f services subscribed, the quality of service (QoS)

requirernents, the b i b g idonnation, and the cumnt locations of the MTs. For each

subscriber there is a pointer to a Visitor Location Regista to assist routing incorning

calls. There is logically one HLR per GSM network, although it may be implemented as a

distributed database.

V~srtor Lucorion RegMer:

The Visitor Location register (VLR) is a dynamïc dadxae, whose entries change as

subscriber move within one or more location areas (group of cells). VLR contains

detailed information on Iocaîion anà Service data regardhg those MTs entering its

average area for the muting of iaooming and outgohg calls- The VLR also obtains

subscriber parameters h m the HLR and updates the HLR regardhg the status of

suppkmentary semices, if needd Aithough the VLR can k impIcmented as an

independent entity, al i manufhcturers of switching equipment t&e implement the VLR

together with the MSC. The c o m b i i o n of the VLR and MSC speeds up access times to

information thai the MSC requires drPing cal1 processing.

The Authentication Center (AuC) is a strongiy protected database that handles the

authentication and encryption keys for every single subscriber in the HLR and VLR The

Authentication Center contairis a register cded the Equipment Identity Register (ER)

**ch identifies stolen or huddently alterad phones that transmit identity data that does

not match with information contained in either the HLR or VLR

2.1.2 Locution Management PIocedwes in GSM

For mobility management, GSM takes the intemediete approach between full-system

paging and per-cell location updating, using location areas and paging areas (which are

equivalent in GSM) made up of one or more cells [25]. The actual assigrnent of cells to

location areas is operator-defineci, and ïs wnstrained only by the fmt that a location area

cannot contain cells belonging to more than one MSC.

Location Uphte and Registrafion:

Location updating is the procedure for keeping the network infomed of where the mobile

is roaming. Location updating is always initiateci by the mobile terminal on either

detecting that it is in a new location area by periodically monitoring the location

information broadcast by the network on the broadcast channel, and cornparhg it to the

information previously stored in its memoiy, or by receiving an indication h m the

network it is not known in the VLR upon eyiag to estabiish a mobility management

comection. No lofetion updatcs are nquirrd whüe roemiag within the same location

area.

Location updates and location registrations are very similar, and ciiffer only in additionai

daîa t r a n s f d on the network side for location registrations. If the mobile terminal

registm at a VLR for the £ïrst time, no subscnber information exist there yet, and it must

be requested fomi the HLR For location updates between location areas under the same

VLR, the subscRbcr information already exists.

The steps involved and messages exchanged for location updating are illustrateci in

Figure 2.2, and explained below:

1. The mobile terminal must fÜst be synchronîzed to the base station, to be able to

receive and decode Broadcast Control Channel (BCCH). The BCCH broadcasts

information necessary for MT to be able to properly access the network, including the

identity of the network, location area, and cell, idonnation for handoff and ce11

selection, information describing the cumnt wntrol structure, parameters for properly

transmitting on the random access channel, and other ceU options.

2. The MT transmits a CHANNEL-REQUEST message on the Random Access

Channel (RACH). This message contains only 8 information bits in total, and

includes the teason for the mobile access (3 to 6 bits) and a randorn discrirninator

used to prevcnt duplicate channel assignments. In this case, the reason for access is

location updating.

3. If the= is no collision of the access burst, and the MT is not bamd h m accessing the

1s

LA or ceil, the B a Transceiver Station (BTS) measures the Uansmission delay, and

sen& a CHAANE - REQUIRED message to the Base Station Controllci (BSC).

4. The BSC selects a signaling cbimnel @ossibly hill rate) and sends its description in a

CHANNEL-ACTIVATION to the BTS. If the BTS is able to allocaie thaî channel, it

responds with a positive CHANNEL-ACTIVATION ackiowledgement.

MS BTS BSC MSC VLR HLR VLR(Ptcvious)

Figure 2.2: Message Exchange for GSM Locution U w e s .

if the BTS charme1 activation was successfbî, the BSC wiiI fonmrd an

IMMEDMTE-ASSIGN commmd to the BTS, which forwards it to the MT as an

IMMEDIATE_ASSIGNMENT message, describing the assigned radio chamel, on

the Access Grant Channel (AGCH).

The MT accesses the assigned channel, using the given timing advance and power

control parameters, and traasmts an initial message uidicating its identity ([MSI or

TMSI), the mobile .quipment classmark (indicating its capabilities), and the type of

location update in a LOCATION-UPDATE-REQUEST message. (This layer 3

message is acnially piggybacked on a layer 2 fiame, whose ackmwledgement

establishes the layer 2 conneaion and tes0Ives any access contention issues that may

ex&)

The BTS sends an ESTABLISH INDICATION message to the BSC contirming the

setup of the channei, and carrying the layer 3 location update request idonnation.

The BSC sets up an SCCP (Sigoaling System No.7) connection with the Mobile

services Switching Center (MSC). At this point, the MT can communicate with the

MSC. Communication between the MSC and the MT is forwarded transparently by

the base station subsystem. The BSC forwards a COMPLETE-LAER 3-INFO

message to the MSC, which wntains the location update request information fom the

MT.

The MSC uses the Mobile Application Protoc01 (MM) to commuicate with the

appropriate location registers to complete the location update. The MSC sentis a

WMAPUPDATETELOCATIONNAREA message (service request, technically) to its

VLR, &ch includes the information received h m the MT, such as the IMSI or

TMSI, the location update type, and the new Lacation Area Identifier (LAI).

10. At this point, a few optional procedures may be invoked These include authentication

of the mobile, activation of the ciphering mode, and verifidon of the International

Mobile Equipment Identity -1) status to ensure that the h4T itseif is not Iisted as

being stolen or incompatible. These procedures will not be described here, but their

presence, and additional signahg Ioad, shoald be noted.

1 1. I f the MT is allowed to register with the VLR, the subscriber's HLR is notified of the

change in VLR area through the MAP-UPDATE-LûCATiON service request. Some

variations are possible hem, such as if the MT included its TMSI in the location

update request the previous VLR would be queried to obtain the subscriber's IMSI

(since TMSI is only valid in wnjunction with a LAI). In that case, subsequent

procedures, as describeci here, would be slightly modifie& since a TMSI realiocation

may be invoked The e c e identification to the HLR includes the IMSI and VLR

address.

12. Upon receiving the MAPJJPDATE_LOCATION service identification, the HLR

sen& a MAP-CANCEL-LOCATION request to the subscriber's previouus VLR This

deletes any subscriber information h m the previous VLR, which then sen& a

MAP_CANCELLOCAnON acknowledgement to the HLR-

13. The HLR then sen& a MAPMAPINSERTTSUBSCRIBERUBDATA request to the new

VLR Clearly, if the subscriber registers for the first t h e in the new VLR, no prior

subscription information wiil exist. This request sen& information such as the

subscriber's MSISDN, the type of Nbscni Services, details on subscnbed

supplementary d c e s (such as caii foMlardiag address), and any restrictions on the

subSCTiber (such as toaming, or operator detedeci barring). This information is

necessary for service provision by the new VLR and MSC. Upon receipt of this

information, the requcst will be acbiowledgernent by the VLR

14. Once the subscription information is slightly aeknowledgement by the new VLR the

HLR will have completed the l d o n updatiag, and wül acknowiedge the

MAPMAPUPDATETELOCATiON request previously sent by the new VLR, which in him

will acknowledge the previous MAPMAPUPDATETELOCATIONNAREA request that the

VLR tiad received h m the MSC.

15. Upon completion of the network side location updatiog functions, indicated by the

MAP-UPDATE-LOCAnON-AREA aclnowledgement, the MSC will send a

LOCA~ON-WPDATE-REQUEST message to the MT. This message is

transparently forwarded by the BSC and BTS, using the Direct Transfer Application

Part (DTAP) over the existiiig dedicated signaling connection to the MT.

16. The location update is now complete. Unless the MT had previous1y indicated that it

wants to maintain the existing signalhg 1- or the network quires it for any

additional signaLing, the link is released when the MT receives a

CHANNEL - RELEASE request b m the network (or the MT timer for receiving this

message expires).

Interr01~uftion and Paging:

By definition, a mobile subscriber is not k t l y assoCiated with a fixeci telephone link.

When an incoming cal1 h m the fixed network @SN) is direct& at the mobile network,

the currently senring MSC for the target subsCnber must be fomd, and a wnnection must

be established to tbat switch for the duration of the call. This is the generai call routing

procedure, and interrogation is the mobile network fùnction that determine what MSC the

incoming caii shouid be routed u>.

As described previously, the mobiie network maintains the currmt location of the

subscriber in the HLR. Typidy, because of legal, administrative, or technical reasons,

only certain mvitches are designated as Gateway MSCs (GMSCs) which are able to

directly query the HLR to obtain information for mobile terminating calls. GMSCs,

usually in the destination subscriber's home mobile network, receive incoming calls nom

the PSTN, query the appropriate HLR for the intended subscriber's current location, and

forward the dl to the proper destination MSC. Aithough not technically impossible,

PSTN switches are generally not able to ditectly query GSM network databases, such as

the HLR

As for the description of location updates, the mobile terminaihg cal1 setup procedm

described below and shown in Figure 2-3, is for the most case and assumes a successfid

outcorne-

1. The onginaihg PSTN switch wilI be able to derive address of the GMSC h m the

dialed digits (the intendecl mobile subscriber7s MSISDN), and will send an ISUP

Initial Address Message 0 to the GMSC indicatirig an inwming call.

2. The GMSC is able to derive the desthmion subscriber's HLR h m the first few digits

of the MSISDN. The GMSC will scad a MAIMAPSENDEM)ROUTMGOINF0RMATiON

reqwst, with the destination MSISDN, to the HLR The GMSC uitimately requires a

roamhg number WSRN) which it can use to route the cail to the destination MSC.

3. The HLR maps the MSISDN to the IMSI, and look up the cumnt location of the

destination subdber-. This a d w s is n o d y in the fonn of the address of the

subscriber's ~ t r n t The HLR sen& a MAP PROVIDE ROAMING-NüMI3E.R

request to the cumnt KR, giving the IMSI of the subsaiber and the cumnt MSC

(which is generally ignored, since there is in practice a one-to-one relationship

between VLR and MSC).

4. The VLR aüocates a roaming number (MSRN) fiom its assigned pool, and rnaps the

IMSI to the MSRN. A q n s e with the allocated roaming number, to

MM-PROVIDE-ROAMING NLTMBER requea is sent to the HLR

5. The HLR forwards the MSRN to the GMSC in response to the

MAP-SEND-ROUTiNG INFORMATION request. The GMSC is the able to

continue with the cal1 routing, and se& an IAM to the destination MSC, with the

new MSRN.

6. Upon receipt of the IAM, the MSC sen& a MAPMAPSENDENDINFOOFOROINCOMING

CALL request to the VLR *ch indicates the MSRN and any otha information that

may have been hchded in the original IAM message, such as bearer service type. A

~esponse to this rcquest is not fortvadeci to the MSC util the subrriber has

successfuily responded to the paging.

Receipt of the MAP-SEND-MOFOR-mC0MINGCALL request triggers the

VLR to issue a MAP-PAGE request back to the MSC. This request to page the

mobile station includes the IMSI of the destination subscriber and the LAI that is

stored in the VLR

The MSC sen& a PAGING message to the appropriate BSCs, which includes the

IMSI, TMSI (if one has been allocated), a list of the cek to be pages, and, if

applicable and known, the type of c h e l rrqugcd for he hwdng cal1 (e-g., speech

or data).

MS BTS BSC MSC VLR HLR GMSC

Figure 2.3: Message Ekchmge for GSM Interrogation und Paging.

9. The BSC sen& PAGINGGCOMMAND messages to each BTS specinecl in the

previous PAGING message. The PAGING-COMMAND message includes the

identity of the mobile subscriber (IMSI or TMSI) to be used, the paging group of the

subscriber, and the type of channel requirrd, if applicable.

10. Paging groups are sections of the complete paging channel, in which di paghg

messages for particuiar groups of subscribers are normally sent. S i n a mobile

termlliats, in generat, need to listen only to thek own paging group, and a paging

group is much shorter (in tenns of the number of transmitted timeslots) than the

cornpiete paging channel, less time û spent Listening to the paging channel, thus

conserving battery power. This concept is known as discontinuous reception.

1 1. There are three types of PAGING-REQUEST messages that may be tranSI11itted over

the radio interfi. These ciiffer in the type of identifier OMS1 or TMSI) used and the

number of paging requests that may be sent in one message. Ail messages are 23

octets (184 bits) long, and since a TMSI is shorter than an IMSI, more TMSI paging

requests can be sent per message (up to 4 with a PAGiNG-REQUEST-TYPE 3

message). Due to the unpredictability of the radio environment, paging messages are

n o d y repeated an operator-conf&urable number of times, to decrease the chance

of lost pages (for example, if the subscriber was temporarily in a shadowed am.)

12. When the MT successfully d v e s a paging message, it initiates a channel

assignment procedure, identical to the f k t few steps of the location update procedure,

with the exception that the establisbmt cause is 'respoox to paging' ïnstead of

'location updatc'. A context is maintained on the network side to complete the circuit

for the cal1 once the MT has responded to the page and a radio-signaling Link has been

establistied

Until the early 199ûs O.S. cellular customers that m e d between different cellular

systems haà to register manually each time they entered a new market covered by a

different senice provider, diiring long distance tmvel. This required the user to call an

operator to request registration. In the early 1 WOs, US. cellular carriers implewnted the

network protocol standard IS41 to d o w different cellular systems to automatically

accommodate subscribers who roam into their coverage region. This is called

intemperator roaming. IS41 allows MSCs of dinmnt semice providers to pass

information about their subscribers to other MSCs on demand.

IS-41 relies on a feature of AMPS (Advance Mobiie Phone Services) called autonomous

registration. Autonomous r e g i d o n Û a pocess by which a mobile notifies a serving

MSC of its presence and location. The mobile accomplishes this by periodically keying

up and transmitting its identity information, which allows the MSC to constantly update

its customer list. The registration command is sent in the overhead message of each

control charnel at five or ten minutes intmals, and includes a timer value that each

mobile uses to detemiine the precise time at which it should respond to the serving BS

with a registration transmission so that the MSC can validate and update the customer

list. I M L aiiows the MSCs of the neighbring systems to automatically handle the

registration and location validation of roarners so that users no longer n a d to manuaily

register as they travel. The visited system creates a VLR record for each new roemer and

notifies the home system via IS-41 so it can update its own HLR

The 1s-41 and GSM location management strategies are very similar, except for the

folIodg differences. In GSM, when the new VLR receïves the registration dErmation

fkom the HLR, it assigns a new TMSI to the M ï for the new location area The HLR also

pmvides the new VLR with all relevant subscriber profile information required for caii

handling as part of the afnrmation massage. Thus, in contrast with 1s-41, authenticaiion

and subscriir profile infoRnati011 are obtained nom the HLR and the oid VLR, not just

the HLR

The procedure for delivering cak to mobile users in IS-41 is very similar to that in GSM.

The sequence of messages between the der's and cailed party's MSCNtRs and the

HLR is identical to that show in d flow diagrams for GSM, although the names and

contents, and lengths of messages may be diffmnt, see 1261 for more detailed

descriptions of the IS-4 1 mobility management strategy.

2.3 Conclusions

The detailed operation of the location management procedures in a practicai mobile

network, specXcally a GSM network, serves to show the considerations that must be

taken into ac«>unt when developing new location management algorithms. For example,

many proposais do not consider that at pfe~ent, and likeiy for several years, mobile

networks and fixed networks are disjoint. They do not have integrated switching and

signaling hctions, due to not only technical constraints, but also legal and

adminisirative ones.

At this point, it shodd be notai that location updating, interrogation, and pagllig are

relatively complex Ui terms of signalhg on both the radio interfàce and within the fked

network, and that there are several factors that should be considered for an efficient

location management scheme. Some of the practical issues will be discussed in the

literature review in Chapter 3.

Chapter 3

Previous Work on Location Management Proposals

with Classification

Emerging mobile and PCS enable communication with a person at any time and at any

place. PCS introduce three capabilities: termid mobility provideci by wïreless access,

personal mobility b a d on personal numbers, and service mobility through management

of user Service profiles. Mobility management is an important issue in PCS. One of the

main tasks of mobility management is location tracking. Location tracking fiinctions

provide PCS with the methods to keep the location of mobile users and termjnals. In

PCS, subscriber mobility is wntrolled t h u g h location registration and update. The

overall location management fiznctioaality is compriseci of three intet-related aspects of

Iocation updating, interrogation, and paging. Different researchers have concentraid on

different system resources (such as database storage capacity), quaiity of seNice

parameters (such as call setup delay) etc. The proposais are evaluated in ternis of the

overail goals of location management:

Minimize signaling, both over the radio interface and within the network, to teduce

bandwidth and in- capacity.

. . . Muumue caii setup Qlays in order to maintain acceptable quaiity of service.

. . . Minunue the amount of data stored for esch subscriber, to d u c e equiprnent cost.

. . . Muumue the computational complexity of algorithm, to duce hardware costs,

conserve battery power. and improve response times etc.

In general these goals are coaflicting and trade-offs must be made. Typidy, proposais

concentrate on improving one paaicuiar aspect by compromisiag on another.

3.1 CIussificotion of Location Management Sbotegies

Different propos& exist with the goal of improving some aspect of location

management Some concentrate on improving signaling and querying efficiency of the

network-side while other concentrate on reducing radio interface signalhg in t e m s of

paging. Thus location management proposais f& in two broad categories: those that

concentrate on the interrogation aspect of location management and those that focus on

location updating and paging algonthms. Figure 3.1 shows our classification of location

management schemes.

3.1.1 Location Upddng and Paghg Roposufs

Location updaîbg and paging algorithms focus on reducing the overail number of

location updating and paging messages sent over the air interface to minimize the totai

location management cost. This can be achieved if the location of the mobile user is

known in advance, so that iastead of sending paging messages to aii the cells in the LA,

only the cell hosting the subscriber is paged.

Current PCS networks partition their coverage areas Uno a number of LAS. Each LA

consists of a p u p of d s , and each MT pedomis a location update when it enters a LA.

Location Management Strategies

Location

Variations in hplementing Location Updating Location Areas with Alternative

Static Dynamic Time Distance Movement

Figure 3. I r Clars~cation of Location Mùnagemeni Proposcls-

When an incoming cal1 arrives, the network Locates the MT by siniultaneously paghg ail

cells within the LA. Th- are a number of inefficiencies associateci with this location

update and paghg scheme:

MTs that are Locaîed aroimd LA boundaries and make muent movements back and

forth between two LAS may perfonn excessive location updates.

Requiring the network to poil aii the cell witbin the LA each time a cal1 arrives may

resuit in an excessive volume of wireless broadcast m c .

The mobility and cal1 arrïval patterns of each MT vary, and it is g e n d y diacult to

select a LA size that is optimal for ai i users.

The location updating and m g sûategies can be divided iato two categones; one that

makes use of LAS while the other one does not,

3.I.l. I Variations in I~Iementing Location Areas

h the conventional location-updating methods like GSM, cells are grouped to form

disjoint LAS; these are disjoint in the sense that one ceil is included in only one LA.

Location areas aliow the system to track the mobiles during their roaming in the

network(s): subscribet location is hown if the system knows the LA in which the

subscriber is locatd When the system has to d l i s h a communication with the mobile

(to route an incornhg d l , typically), the paging only occurs in the cumnt LA. Thus

resource consumption is limited to this LA; paging messages are only transmitted in the

cells of this particular LA. To provide additional capacity, while constrained by the fixeci

available radio specûum, operaton have been using progressively smailer oells, through

ce11 sptitting and sectorization. To accommodate this trend, either the number of cells and

submibers per location area mrin increase (to maintain the same geographical size for

the location areas), or the geographicai size of location areas mut decrease (to maintain

the same number of cells per location azea). Assuming the wrmt subscriber mobility

patterns and location management algonthms, the number of paging messages wiU

increase in the former case, and the number of location updetes will bcrease in the latter

case.

The above s i w o n arises because location areas are geographidy fked, and apply to

all subscribers, regadess of th individuai subscriber mobiity ppttenis. This can be

illustrated by considering an exampie with a fiut subscnber (for exampie, driving a car)

and a slow subscriber (for example, a -an). The fast subscriber may cross several

location areas during a trip, while the m a n may not even cross one. The fast

subscriber can be handled efficiently by aeating large location areas to avoid numerous

location updates. However, if thae large location areas would also apply to the

pedestrians subscr i i , significant signaling would k wasted piiging over the entire

location a m , when paging over a much srnalier location area (or smallcr m g areas

within the location area) would suffice.

The LA-based location update and pa@g scheme is a static scheme because it cannot be

adjusted based on the parameters of a MT h m tirne to tirne. One of the pmblems with

this scheme is that location and paghg amas are stat idy d e W . The detemiinaton of

which celi belong to whifh location areas (and implicitly, paging areas, since the two are

usually identicai) is t b u g h a spatially and temporally static procedure using aggregate

data.

In [II, an intelligent method for locating users, d e d an Alternative Strategy (AS) is

intrduced. This proposal is bascd on the observation that the mobility behavior of a

majonty of the users can be predicted. The strategy c m d u c e sipnaiing messages

involved in mobility management proceduces, leading to savings in system resources.

This approach reinforces the information capabilities ofthe system, and provides tools for

prediction by integrating (ùi the system) more information about tbc extexnai world.

The user profile may be buiit up by monitoring the user over some period of t h e . This

long-terni user profile seldom changes, although the achial updating procedures are not

specified. The location accuracy may be improved by mordering the pagïng areas in the

long-temi profile according to short-temi or medium-term algorithms, or by paging

concentrically around the last known location area. The former approach attempts to

reorder the paging areas so that areas asociated with a higher probability of containing

the subsCnber are paged fïrst, reducing signaling and delay. Call arrival and origimtion

rates f?om particular paging areas may be used for a medium-tem reordering of the user

profile. AiteRlSitively, estirnateà distance tmreled since the last known location may be

used at the tirne of an incoming di to determine which areas to page first The paper

rnentioned th* with this approach, and using dinerent mobility models, parameters and

evduation methods, very high signaüng swings have beea reported.

Gregow P.Poilrrri and Ckik-Lin 1:

The strategy in [2] proposed a Rome-Based Strategy (PBS) to d u c e the signaling

trafic on the radio ünk by increasing the inteiligcnce within the h e d network- The

system maintains a sequential list of the moa likely places where each user is located (in

tenns of a given set of LAS). The list is &ed h m the most to the least likely place

where a user is fomd When a c d anives for a mobile, it is paged sequentially in each

location withi. the list. When the user moves between location areas in this List, no

location update ïs required, The lin may k pmvided by the user or may be based on each

user's past mobility history.

The Profile-Based strategy relies on the observation that most users follow regimented

daily schedules that can be exploited to estimate their curent location. If the system

knows that at a given tiw the user is most likely to be in a certain location a m , second

most likely to be in a second location area, etc., the system can maintain a List of Wely

locations ordered fiom most to 1- likely. When a cal1 arrives for a user, it is paged

sequentially in the order indicated by the list.

In [3], an analytical fnunework is presented for analyzing the performance of different

schernes for Location management. ThÏs paper considers two paging methods together

with location updating techniques. The paging techniques considered are simui~mous

paging and se~uentiai paging. In case of simultaneous paging, ail celis inside a LA wiii

be paged simuitaneously when there is a caü to any one ce11 in the LA. In sequential

paging, paging is done in k-ce11 PAS sc~uc~ltially until the callad MT is foimd The

paging tranic depends on the average number of paged cells till the MT' is located This

formulation leads to a closed fonn expressions for the cost of location management in

tenns of the d-arriva1 rate, boundary crossing rak, the size of the LA, the maximum

acceptable average paging delay, the total number of celis controiled by the Mobile

Switching Center (MSC), etc.

It is suggested that the best strategy is sequential paging combined with some intelligent

feahires. As suggested, useiùl information related to the MT, such as the most recent

interdon area and its speed, can k kept tmck of, and this information can be used in

carrying out the paging process. This extra idormation wil l increase the probability of

fmding the MT in the fint area paged. Of course, this depends on the user spad and the

t h e lapse between the last update of user location and cal1 received. Paging is still done

sequentidly, and the dinenace resides in the way in which the paging base stations are

selected (Le., the added 'intelligence'). This inteuigent paging does lead to a c o a

reduction compareci to random sequential paging at an expense of extra complexity.

fi-Bing Lui:

The proposai in [4] studies a special case of AS [l] called the Two-Location Algorithm

(T'LA). In TLA, two locations to track the location of the MT are considered. On the

other han& AS allows more than two user locations in the profile. When a phone cal1

arrives, two LA identifiers are used to find the actual location of the portabie. The order

of the identifïers selected to locate the MT affects the performance of the algorithm. The

MT has a small built-in memory to store the identinm for the two most recently visited

LA'S. The record of the MT in the Home Location Register (HLR) also bas an extm field

to store the correspondhg two locations. The f h t memory location stores the most

recently visited LA.

When the h4T joins the network, the location is storeci in its memory, and a registration

operation is required to modify the HLR record. When the MT moves to a new location,

it checks i f the new location is in the memory. I f the new location is not found, the

identifier for the LA that the MT just lefk is kept, and the other address is replaced by the

address for the new LA. A registration operation is rquired to make the same

modification in the HLR record. If the addsess for the new location is already in the

memory, no registration operation is performeci. The order of the addresses selected to

locate the portable affects the performance of the algorithm. If the MT is located in the

first try ( r e f d to as l d o n hit), then the paguig cost for the TLA is the same as the

IS41 algorithm. Otherwise, an extra pmalty is incurred by TLA to locate the MT for the

second try ( r e f d to as location miss; the second try is always successful). Mer the

second try, the HLR identifies the LA where the MT is visiting.

Recent research efforts focus primarily on dynamic location update mechanisms, which

perfom location ripdate based on the mobility of the MTs and the fiequency of incoming

calls. Several pmposals suggest the use of user profiles to individuak the location areas.

A personal, or individwihd, location area, anchored a r m d the ce11 in which the

location update occurs, would consist of the most Wrely cells that the subscriber couid

traverse. The infortnation to create the personal l d o n area is derived h m the user

profile, which contains a record of previous transitions h m ceii to d l , together with the

length of t h e spent in each cell. Some location management proposais are baseà on

grouping subscribers with similar behavior. Other proposais consider the use of multiple

LA leveIs to track iocations of mobile tenninals. The nominal LA sizes at each level are

different Each mobile terminal is registered at a LA of suitable level, and the registered

level is dynatnidly changed according to its past as well as present mobiüties.

Anna Errc rurdXkm =ou:

The proposecl algorithm in [5] ailows a MT to trammit update messages only at specific

cells (the number of which is s d , cornpared to the total numbcr of ceils in the

network), while restricting every search for a mobile user to a small subset of cells.

In a simple cellular network, there is one base station per cell and a large number of base

stations in the system. In the proposed scheme, a subset of base stations d e d reporting

centers is selected among al1 base stations. The cells associa with these base stations

are referred to as reporting cells, while other ceiis are cded non-reporting celis. The

vicinity of reporting ceii i is the collection of al1 non-reporting cells that are reachable

from cell i without crossing another reporting ceU. Atm, ceLi i is in the vicinity of itself.

The fkquency witb which the mobile usen enter a reporting ce11 conesponds to the

updating cost for the cell. The higher the frrsuency, the higher the updating cost. If the

ceil with highest fbquency is selcctad as a non-reporting cell, the users do not need to

upàate theV location wheneveer they enter tbis ceU- This reduces the total updaing cost by

the largest amount for the entire network. This step is continueci, and the celi with the

highest fkquency among aii remaining reporting celis is reselected. This procedure

continues until ail cells are t r i d

The proposed stmtegy provides a partition scheme to optimize the size of the location

area domain. Simulations are pccforrned to compare the pedomÿioce of three schemes:

always update, aiways seaich and the proposed scheme. The resuits show that the

proposed scheme perfoms better than the other two.

LR Hu and SSAtappoporf:

The paper in [6] proposes an efficient multilayer mobility management scheme that is

especiaily suitable for hierarchical cellular stnictures. The scheme accounts for pst as

weli as present terminal mobilities and dynamically changes the hierarchical level of the

location area to which the mobile terminal registers. ïhe nominal LA sizes at each level

are different. Each mobile terminal is registered at a LA of suitable level; highly mobile

temiinals such as an aircraft will tend to register at the highest level where location areas

are formecl by spotbeams, Low mobility terminals such as pedestrians will tend to register

at the lowest level where location areas are fomied by microcells or clusters of

microcells. The location-updating rate that is genemted by a mobile temiinal tends ta

rernain fixed over a wide range of temünal mobilities.

The system uses multipie rrgistration levels to track the locations of mobile terminah.

Based on the dweli t h e , time that an active MT stays in the LA of a given registration

level, of a mobile terminal in the prcvious LA, a mobile terminal is switched to a suitable

level of location management. Mobile terminais tracked by the proposcd scheme are seen

to generate signaüng wfnc at a very stable rate over a broad clas of terminal mobility.

This fature may prevent the system fiom excessive signaling t d i c due to high mobility

usm and can be used to set the requïred long-term total sigoaling n.afnc.

Thomas Kunz and John Scourk:

The proposal in [7J disasses a stochastic mobility model based on daily activity patterns,

providing a redistic balance ktween completely detenninistic and completely random

mobiity moâels. Activities, together with their location and duration, are selected ushg

subscriber-specific data, as well as randomly selected &ta h m tables derivecl nom

trafic planning surwy deta The path to the next activity's destination, represented as a

sequence of traverseci radio cells, generates cell crossings used for location update

rneasurements. The cunent location of simulated subscribers is continuously tracked and

used for paging measurements.

The model was used as a tool for developing a location management algorithm utilinng

user profiles for the dynamic d o n of location and pagïng areas. Based on the number

of times a subscriber had moved fiom the current cell to the neighboriag cells a personal

location area is dynamically defined during a location update. A history of the average

time spent in each ce11 is used dynamically to determine a subset of cells within the

personal location area most likely to contain the subscriber, and whicb is paged first

The proposed algorithm is comlrirr#i with the aigorithm currently in systems like GSM. It

is show that the proposed algorithm significantly d u c e the total signahg cost, for

nearly all different subscriber types dehed, levels of incorni. calls, woik location

variability, and dynamic location area size as compared to currenly used techniques.

AU prrviously d i s d variations in LA implcmentaîio~ls rcly on the same location-

updating mechanism: a location updating procedure is pdomed if the MT exits its

curent LA; psging is always p e r f o d inside the LA. Other location-update schemes

have been proposed that do not require the division of the network average ana in LAS.

The only location information available to the network is the last point of contact with the

MT, either because of a location update, a connection, or another MT-Network

interaction. These non-LA~riented location-updating methods are inherently

individualized, which would permit parameter opthizaîion for each user individually.

Several dynamic location update and paging schemes are described below:

The tirne-based location update m& [8] is the simples because it just requires the

mobile to periodicaiiy transmit its identity to the network without regarding to its

mobility and incornhg cal1 arriva1 rate. Each MT has a tuner ninniog. On expiration of

the timer, a location update is performed and the tirner is set to zero, and then begins to

nin again. Whenever a user is looked for by the system, it is first searcheci at the ce11 it is

iast reported to, say i. if it is not found thm, thni it is seamhed in cells i + j for wery j -

Accordhg to the movement-based strategy [8], each mobile user counts the number of

cell boundary aossings and updates its location when the count exceeds a predenned

parameter M (this number is r e f d to as movement tbreshold). When a mobiie is

paged, it can be fond within a neighborhood of atmost M celis away h m the previous

reporthg cell. In this case, each mobile needs to keep track of the number of cet1

boundary crossings since its last location +te.

Distance-ked:

In a third propasai, a MT performs a l d o n update when its distance h m the ce11

where it perfonned the last location updaîe exceeds a predefined value D (this distance

value is refened to as the distance threshold). A distance-based location update scherne is

considered in [9]. The authors introduce an iterative algorithm that can generate the

optimal thrtshold distance, which d t s in minimum cost. When an incoming dl

k v e s , cells are paged in a shortestdistance-ffirst-order such that ceiis closest to the ce11

where the last location update occumd are poileci m. The delay in locating a MT is

therefore proportionai to the distance traveled since the last location m e . Resuits

dernonstrateci that depending on the mobiiity and cail arriva1 parameters, the optimal

movement threshold varies widely .

One study [IO] compareci thrte difEerent location updating strategies with respect to the

update costs, paging costs, and total costs of tracking mobile users by constructing an

objectaienteci environment in Java In their cornparison of the différent update

strategies, the authors claim thai the distance-based methd gïves the lowest combined

location updaîing and paging cost.. The the-based strategy causes updates periodicaily

independent of how a user moves, so the update cost of this strategy is steadïer than that

of the other strategies. However the paging cost increases rapidly in proportion to MR,

the Mobiiity Rate, which is defiwd as the average number of ceils changed by the user

per unit tirne-

In case of movement and distance-based strategies, for low the update coats of these

strategies are smaller than, and the paging costs are larger than that of the tirne-based

strategy. While, for a high MR, these strategies resuit in larger update cost and smalla

paging cost than the tirne-based strategy.

Severai proposais have attempted to impmve the signaliag and querying efficiency of the

network-side database queryuig rquited by location management, with a secondasy goal

of reducing radio interface signalhg in terms of paging. The driving requirement is to

remove the bottieneck that may &se as a d t of a centralized HLR, which must be

queried for every incoming cail and eveq location update associated with the subscriber.

LA partitioning, and thus mobility menagement cost, p d y dies on the system

architecture (e-g., database locations). Designing an appropriate database organhtion can

reduce this signaling t r a c .

Research in the area of database architectures generally falls into two categorics. First,

extensions to the GSM location management strategy are developed which aim to

improve the GSM scheme while keeping the basic database archi- mchangd This

type of solution has the advantage of easy adaptation to the current PCS networks without

major modification. Anotthcr category of rtsearch mults in completely new database

architectures which require a new set of schemes for location registration and cal1

delivery .

Three kinds of network database architectures are cloxly rdated to mobility management

schemes. The fkst is a centralid database architecture- Al1 user information is stored in

a central database. This architecture is simple and bas the advantage of easy operation and

control, if it is applied to a system that provides compamîively srnail-sale service in a

limited area.

The second architecture is a hierarchical (distributed) database architecture which uses

several independent databases accordhg to the geographicai pmximity or service

providersers The two level HLRNLR architecture as described in GSM 1251 and

1s-41 [2q standards are replaced by a large number of location databases. The location

databases are organkd as a tree with the mot at the top and the leaves at the bottom.

Each leaf4evel &tabase sesees a location registration area and stores user informaiion.

Each database in the higher-levels stores pointers to the next lower-level database that

stores user idonnation or has a pointer ta a lower-level database.

The third case is the hybnd database architecture that combines the cenîraiized and

distributed database architectures. In thls case, a centrai database (HLR-Iike) is used to

store a i l user information. Other d l e r chbases (VLR-like) are distributed aU over the

network. These Visitor Location Re&- (VLR) da?ahes store portions of HLR user

records. This c m lower the congestion probabïlity in the HLR to some degree but has

overheads in multiple database operation because the VLR has to obtain MT information

from the old VLR and delete it in the old VLR. A single GSM network is an example of

such architecture. In some cases there can be more than one FERS distributed in the

network.

3.1.2.1 Dàstràbufed Database Architecture

Jan Jannink, Derek Lam, N~~oyonun Sivukumcrr, Jennger Wdom a ~ d Dondd C.Cox=

The basic idea behind [ I l ] is the concept of me-long numbeiing without making use of

HLRNLR In IS41 and GSM, each subscnber is assigned a phone number fhat contains

enough infoxmation for the network to derive the location of the HLR These phone

numbers are, therefore, geographical and are tied to specific HLRs.

In a basic hierazchical model, each leaf4evel database services a zone and stores profile

of users located in that u n e . Each database in the higher levels of the hierarchy stores

"pointerst' (user ID + database ID) ta the next lower level daîdmse that stores the d s

profile or has a pointa to a lowa level cbbase. ?hae is a conceptuai "mot" daîabase

that stores a pointer for every user. In practice, the root may be distributed among several

databases so thaî no one Antahace ne& to store aU user pointers or seNice di root level

queries and updates. This simple hierarcbical LMT provides me-long numbering since

there is no concept of a "home site" for a user as in HLRNLR.

When user A calls user B, the Location lookup for B's pmfiie fint pmpagates up the

hierarchy fiom A's zone to the !kt database that c o n t a a pointer to B's profile. The

query then popagates down the hierarchy foiiowing pointers to B's proNe until it is

found in the leaf-levef daîabase that services the zone in which B is currently l~cafed.

When user A moves fiom the current zone to another wne, the current zone ships a copy

of A's profile to the next zone, and defetes its own copy. The A.rtahases dong the path to

the least common ancestor of both zones are then upàated so that the pointers to A's

profle reflect the new location of A. The idea behind profile repiication is to reduce the

latency of profile lookup at the expense of increased update and storage CO* Essentidy,

a user's profile is replicaîed at a set of daîabases such that the benefit of local lookups at

these databases outweighs the update cost due to the user's mobility. For this the

aigorithm cornputes the Local C d to Mobility Ratio (LCMR) of the subscriber, defïned

as the number of calls f h n a particular switcil to a particular subscriber, relative to the

number of location updates penormed by the subscriber. If the LCMR is greater than

some predefined riinimum tbreshold value, the user profiie is replicated.

In [12], the authors developed another LMT, Hierarchicai Mine Parametric PronlE

Replication (HOPPER), that uses a hierarchical organhtion of databases and on-lim

profile replication to achieve Me-long numbering with scalability and efficiency. In

contrast to off-line schemes, the on-üne replication technique uses on-line LCMR

estimates and dynamicaüy mîgraîes replicas to appropriate databases. On-line schemes

have the advantage tbat they can adapt to changes in user calling and mobitity patterns by

dynamically migrating replicas mund the network. Due to practical storage constraints,

it may not be possible to place replicas at all locations where there are expected benefits.

By dynamicaily adjusting the locations of replicas, on-line schemes cm increase the

"usefiilnessn of a replica and schieve the same lodoip @ormance of off-line schemes

with d e r storage requirements.

Slilomi LWev et ai:

In (131, the authors suggested a &ta structure for location management in mobile

networks. The data structure is based on the tree location daîabase stmcture. The

algorithm replaces the root and some higher levels of the tree with another structure that

balances the average load of seamh request The new structure of the upper levels

improves the performance of the tree structure by spreading the load of queries. For this

modification the authors use a set-ary butterfly network which is a generaihtion of the

k-ary buttedly network. The mot of the modified tree has to maintain the location

information for only some portion of the mobile terminais. This inturn keeps the number

of update messages small; only the embedded me for the mobile tennllral for which the

location update message has been sent is involved in the update. The proposai aiso

suggested modifying the lower level of the tree to refiect bettrr neighbor relation between

geograpbic cells to support simple location &ta management. This is done by adding

comections to the lowest level of the tree such that any two MSCs that comspond to

neighboring geographic regions wiU have either a conmion parent or a direct link

connecting them. This may d t in efficient local broadcasts and may support handoffs-

The modification of the lower level supports a handoff procedure d l e d 'follow-me

handoff. The update of the proposed location databe ensures correct location data

following any number of transient faults that corrupt the location database information,

and thus is ~e~stabilizing.

The goal of a location management scheme should be to provide efficient searches and

updates. In [14] the authors present strategies for updates, search-updates and a search

protml. A search-updak occurs after a successfirl search, when location information

corresponding to the searched tenuinai is updated at some terminais. The authors present

several location management strategies based on a hierarchical tree st~cture database.

The structure co11sists of MTs, BSs, and MSCs. The base stations are located at the leaf

level of the tree. Each BS maintirinr iaformation of the temiinals residing in its c d .

There is a unique 'home' address for every mobile rermuial. The home address is the

identifier or name of the mobile terminal. The physical address of a mobile terminal

might change, but its home ad- remairis the same irrespective of the terminal's

location. Each MSC maintains an address-mapping table that maps the home adàress to

the physical address of the MT residing in the subtree ben& i t

The paper presents the results of simulations Camed out to evaluate the perfomance of

various static location management strategies for various d-mobility -S. The cost

metric is the number of messages reqwd for each operation (searc4 update and search-

update). The prformance parameter of interest is the total cost, defined as the sum of

average update cost, average search cost, and the average search-update cost. Simulations

show that perfonning search-updaîes siificantly d u c m the total costs.

3.1.2.2 Hybrid Databuse Architecture

Sliivakumor mà Wrciem:

The proposal by Shivakumar aad Widom [15] discusses replication of the user profiley

containing the subscriber's current location, in severai location registers. Assuming an

integrated network mhitecnite, outgohg calls h m a particular zone (ana controlled by

a VLR) would f k t check the local VLR, in an attempt to avoid querying a distant

centralized database¶ Le., the HLR, for the cumnt location of a specinc mobile

submiber. The decision of where to place the replicated profiles, given the costs for

updating the replicated records, is based on a niinimum-cost, m a x i m d o w algorithm

described in the paper. The HLR maintains the cumnt location of its mobile subscribers,

and manages the ripdatia$ of aU their replicated records.

The algorithm requires the construction of a flow network, which is a graph containhg

nodes for each subscriber and each zone in the network. The edges between the

subscriber nodes and the zone nodes have attributes that requin estimates for the number

of location updatcs p e r f o d by a particuiar subscriber. These estimates together with

estimates on the replicaticm costs and dadmse capacities, are used by the minimum-cost

m;urimum-flow algorithm to determine for which subscribers, and in which nodes,

replication of the user pronle would k cost-efficient. The possibility of varying mobility

and caii arriva1 paaems is considercd, and four algonthms are presented for modifying

the flow network and minimum-cosî, maximum-flow algorithm to avoid having to

recompute the entire algorithm, which is exponentiaily bound.

The Reverse Virtuai CaU (RVC) setup is a rhcme for delivaing mobile tcmiinal cal1

[16]. It allows, d e r the constraint that the LA is not srnaiier than the VLR area, a

reduction in the number of signahg messages exchanged ktwecn the called and calling

databases and switches. The prirnary motivation is that too much effort is king exerted

by the f k d network to track users wbo seldom d v e calls. An added factor is that a

very high perctntage of c d attempts fa1 and consume much of the network resources

~~lllecessarily. The goai of this papct is to deiiver calls without keeping track of user

locations and to min- the cost of Wed cail attempts. RVC combines paging with

physically reverseci cal1 setup to fonn a logically fonuard caii setup.

As in GSMY al1 existing cellular standards allocate networic murces (voice tninks) pnor

to paging a mobile termina. If the terminal does not respond, the network must tear down

these resources. Users who simply do not leave their phones tunied on cause large

portions of failed cal1 attempts- In RVC setup, voice tnmks are not teserveci untii the

mobile is found and willïng to accept the call. Moreover, the signaling load and the delay

incurred by the currently standardized H L R M B method of tracking mobile users are

expected to be high. RVC can function within the exiniag ceUuiar paging network or

within an integrated ovalaid paging netwok In RVC, instead of setîing up voice tnmks

to the tenninating switch w h m the d e e last registered and instnicting the terminating

switch to page the mobile, the signaling system is used to insmict the base stations of the

global paging network to page the network. The poiging signai contains the ID of the

d e r . if the callee decides to accept the cal& the mobile terminal automatically initiates a

cal1 setup to the cder. The c d is routed h m the texmi~ting switch to the originating

switch and is bridged to the cailer. The caiI is completed in such a way that the RVC

feature is tmqaent to both the d e r and the d e e .

Josevk S. M. Ho and lm F. Akv-

A Dynamic Hierarchical Dataôase Architecture for Location Management in PCS

Networùs is proposed in [lq. The proposed scheme ailows the dynamic adjmtments of

user location information distribution based on the mobility and calling patterns of the

MT. A unique distribution strategy is determuied for each MT, and location pointers are

set up at selected remote locations that indicate the current location of the MTs-

Both the IS-41 and GSM standards employ a two-level database architecture consisting of

the HLR and the VLRs. The proposed algorithm introduces a location management

scheme based on a three-level database architecture. Unda this approach, an additionai

level of databases d e d the Directory Registers (DRs) is introdud Each DR

determines the location information distribution strategies for its associatecl MTs.

Location pointers are then set up at selected remote DRs indicating the current location of

the MT. The fwictions of the HLR, the VLRs and the MSCs remain primarily uncbanged.

The distribution strategy for each MT is unique and is determineci baseci on its mobiiity

and caii arrivai parameters. The proposal inttoduces an algorithm for determining the per-

user location information distribution stmtegy, which reduces the signaling, and datebase

access costs for location management. The cost reduction is most significant when the

Local Call to Mobïiüty Ratio (LCMR) is low and the cost of accessing the HLR is high.

It is demonstrateci that the proposed location management scheme results in signincant

saving in both the signaling and database acctss costs for location regisîratïon and cail

delivery. Based on the cost parameters considered in the analysis, the signaling and

database access cost can k reduced by as much as 70./0 and 50% rrspectively, cornpanxi

to the IS-4 1 standard.

RJIwr a d Y-Bhg Lin:

For a mobile which fkquently moves across LAS but seldom has an incoming c d ,

traditional IS-41 registration operation is wastefiil in netwo~k cost since every registration

operation mut update the HLR to record the most ment location of a mobile. Infact,

access to the HLR is much more expensive than access to VLR Based on these

observations, the pointer forwarâing with single HLR (PFSHLR) [18] scheme is

proposed to reduce the waste.

The basic idea is that instead of reporthg a location change to the HLR, wery time the

MT moves to an ana belongiag to a different VL& the reporthg can be ehninated by

simply setting up a forwarding pointer nom the old VLR to the new VLR A mobile

arriving in a new LA sen& a registration message to the VLR of the new LA. ïnstead of

sending a message to infotm the KLR, the new VLR sen& a message to inform the old

VLR about the mobile's departure. On receiving this message, the old VLR deletes the

obsolete record for the mobile and creates a forwarding pointer pointing to the new LA.

When a c d for the h4T is initiate4 the network locates the MT by first detennining the

VLR at the beginning of the pointer chah and then follows the pointers to the cunent

serving VLR of the MT. To minimiie the delay in locating a MT, the length of the

pointer chah is limited to a predefined m u m value. When the length of the pointer

chah reaches the maximum value, additional fowarding is not allowed, and the location

chauge must be reporteci to the Hi& when the next movement occurs. It is demonstrated

that, depending on the mobility and cal1 arriva1 parameters, this scheme may not always

resdt in a reduction in cost k m the original IS-41 schenie.

Yi-Bing Lin and Wen-Nung Tsak

Another scheme combining pointer forwarding with distributed HLRs (PFDHLR), was

proposed in [19]. The basic idea is that in IS-41 the HLR must determine the VLR

currently serving the d e e and query it by sending a route-request signal. Therefore, the

HLR rnay becorne a bottleneck due to heavy signaihg trafnc generated by location

tracking- Lin proposes a pointer forwarding with a distributed HLR (PFDHLR) scheme to

elirninate this overhead in a distributed HLR environment, In this scheme, HLRs are

distributed in remote Public Switching Telephone Networks (PSTNs). Like pointer

forwarding with a single HLR strategy, every HLR in PFDHLR records a LA where the

mobile may &S. When an incoming cal1 is originated nom some ternote PSTN, the

HLR will be directly queried. Next, the HLR at the PSTN queries the VLR recordecl in

the entry associated with the callee. If the mobile is found in this LA, a cal1 wiil be

delivemi, otherwise, the system will tnre the mobile through the forwarding pointer

chain starting from thst LA. This scheme effectively and efficientiy implements the

distributed HLR notation. However, it has some potential side effects. The length of the

pointer chain may increase. Because of the distributcd nature of the HLRs, the total

incoming calls wiU be smed by different HL&. Therefore, the d-to-mobility ratio for

each distributed HLR is VN times that in PFSHLR, where N is the number of remote

PSTNs. The expected length of each pointer chain increases considerably when the cail-

to-mobility ration is srnail.

Kiren-Lhng Sue and CMèn-Chao Tseng:

A scheme considering a one-step pointer forwarding strategy for location tracking in a

distributed HLR enviro~ment is considered in [20]. In this scheme, every distributed

HLR has one record for an authorued mobile. This records the individual LA/VLR where

the mobile was found the last time by an individual HLR DifEerent HLRs may record

different LANLRs as the head of their own locating paths, so they may have different

locating paths; therefore one cellular system with N distributed HLRs may have n

different ïocating pointer chains, n < N, for the same mobile. Whenever a mobile registers

in a new LA, the VLR for the new LA wiU maintain an entry for this mobile. This entry

is the common rear of the n locathg pointer chains. Sirnilar to a double-linked lïst, every

such entq must record the previous nodes in the n locatïng pointer chains. In this rnanner,

the VLR can send a deregktmtion message through ail locating paths. This message is

forwarded to the proper VLR via the previous link in each entry. Nexî, al1 locating paths

are migrated to guarantee that each pointer chain's length among the VLRs does wt

exceed one.

Simulations wcre canied out to compare the three pointer forwafding strategies aawly,

PFSHLR, PFDHLR and OSPFDHLR Simulation results demonstrate that, compared

with PFDHLR, OSPFDHLR can reduce the cal1 delivery tirne/ cost signincandy,

particulariy when the number of distributed HLRs is growing.

The proposai in Dl] explores the use of replicated databases for management of astomet

data (e.g., mobility data, call routing logic) in global, intelligent, and wireless networks.

Two schemes namely full and partial data replication schemes, which are compatible 4 t h

indu* protocol standards (iS41, GSM etc.), are analyzed and a cornparison is made

with the traditional, centralized database scheme. In centraiized database design, al1 call

setup and other signaling hctions access the centralized database in the signaling

network.

The authors considered such mobility services acrou multiple, international networks.

Depending on the anticipted trafEc load and other engineering and economic

considerations, the world is divided imo two or more regions, each of wnich wvers a

group of coutries. It is assumeci that the global customers are based in the United States

and possibly are traveling in a foreign country. A awalized design, whm the customer

Location information is stored in a centraiized database is physically located in the home

country (USA). An identicai pair of Regional (RDBs) is installai in each

region and connected to the U.S. signaling network, e.g., via additional Signai Transfer

Points (STPs)-

The replicated database can be accessed for cail saup and other signaîing purposes as

foiiows. Caus initiated in the U.SA A. query the Home Database W B ) . On the other

han4 for c d s origioatod h m a visited country, quaies are fkst launched to the RDB. If

a c d is destined for a customer visitùig the region, the RDB has the customer record, and

is capable of handling the associated queries. Othenvise, when the RDB carmot find the

needed records, the queries are forwarded over the SignaLing network to the HDB for

f i d e r prcxessing.

The repiicated database design is M e r divided into two, full and partial, data

replication schemes. In the fidl replication scheme, each customer visiting a foreign

region has two complete replicated copies of customer data: one in the HDB and the other

in the RDB. In contrast, in the ceplication scheme, only the RDB keeps a complete

set of customer data, whereas the HDB maintains (replicaîes) only a subset of customer

data that are bfkquently updated. For example, the HDB d a s not keep the location data

for highly mobile, wireless customers visiting a foreign region. The idea of the partial

data replication scheme is to d u c e the overhead of updating certain customer &ta that

are ftequently changed.

The perforrnauce results indicate that the choice of the database architecane for global

seMces depends on the spcific aafnc and mobility parameters such as the proportion of

customers visiting a foreign region, the fiaction of calls generated overseas, the query-to-

update ratioy and the query-to-registration d o . Numerical resuits reveal that the fuîi

replication scheme outpedorms the centrafized one ova a wide range of parameters

mentioned befom. Furthemiore, i f some custowr data, such as location data for highly

mobile customers in wireless networks changes frequenly, and if each cal1 launches

multiple queries into the -y the partial replication scheme offers fiirther

performance impmvements.

It is diffidt to compare d.erent location management schemes since as yet there exists

no absolute bounds on optimum perfo~maace which c m be epplied to any procedute

regardless of assumptions about mobility, network structure, etc. In partïcular, there is a

real n d to obtain realistic performance evaluation models based on acW users'

movements taking into account network structure. Different researchers have

concentrated on différent system resources (such as database storage capacity), Quality of

Service parameters (such as cal1 setup May) etc. There have been several different

approaches to mobility modehg for location management, and some of the methods used

in the literature are reviewed.

Location update rates, cal1 to mobility ratios, and other metrics used in the proposais

depend on some description or model of subscriber movements between location areas- In

rnany cases, some type of random mobility model is used In certain wrs, where the

mobility model is expücitly required in mathematicai derivations, a oneaimensional

model is used to simplify the calcdations.

Static LAS:

Static schemes have the advantage tbat the LA sizes are pre-de- and the= is no need

to implement complex algonthms to caiculaîe dynamic LA size for each subscriber

according to its chanictciistics. The disadvantages are that they cannot be adjusted

according to the parameter of ttic individual user. For example, both slow-mobility

pedestnans and fast-moving vehicles are assigwd the same Sue location areas. SimilArly,

high-mobility time pxiods (e.g., morning nish hou) have the same lofaiion area

assignrnents as low-mobüity time penods, even though signifiant signalhg saviugs

codd be rea l ' i by using larger location areas during high-mobility time penods.

An analytical evaluation of Tabbane's proposal [ I l is given which assumes typical values

for certain parameters, such as cell size, average subscriber velocity, and average number

of cal1 arrivals and di origination. The size and number of signalhg messages generated

over each interface per unit time is the chosen cornparison metric. A simulation is also

used for cornparison. The mobility mode1 is a simple one, with a subscriber moving with

an average velocity and random direction, having a certain probability of remaining in a

certain paging area. The c d arriva1 and origiaation rates an imiformly distributed. The

Mobiiity Redictability Level (MPL) is a key parameter used in the wmparisoas to give

an estimate of the randormess of the mobility patterns, and is given by MPL = z',, p i ,

where k is the number of p@ng areas for the current time period, and pi is the prokbility

of locating a subscriber in area i Resuits were plotted cornparhg the number of messages

across various network intcrfâccs, and the ratio of total cost of the proposeci algorithm

versus the standard GSM aigoriîhm, as a fimction of the MPL.

The main advantage of the AS scheme is to save location updates by storing a wr's

mobility information in profiles. So, the more predictable the user's mobility, the lower

the mobility management cost. Drawbacks are a posïbility of increased peging delay

( d e n the system muçt page a user in merent locations in a sequentiai ma~ltler),

increased memory requirements for storing each user's characteristifs and LA

parameters, and profile updating costs for users, which do wt have long-temi periodic

mobility patterns. In addition, the methods for initializing the user profile, as well as

long-temi updates, are not clearly spifieci.

Gregow P.Pofini d Cllik-Un 1:

The analysis in [2] is the extension of Tabbane proposal [l] that is besed on the fixed

network prformance. Using a general cos formulation, the paper extends that

methodology to study the radio link bandwidth usage, fixed neîworks signaling load, and

cal1 setup deiay.

The proposal gmup people into classes depending upon the predictability of their daily

routine. Although plausible, such puping is fairly arbitrary since subscriber mobility

characteristics may change. In addition the profîle-based strategy of this paper is not

applicable for the random usen and is only applicable to either detemiinistic or quasi-

deterministic users-

The system maintains a List of likely locations ordered fiom most to least iikely. When a

call amives for a user, it is paged sequentidy in the order indicated by the Est. I f a user

moves between LAS in the list, a location update is not required- When a user leaves the

list, it wiil be required to manuaily register with the system. The paper does not discuss

the aigorithm for updating the lisr The benefits achieved by the profile-based strategy are

partially offset by the costs associated with updating the list The cos of list maintenance

is the cost associaîed with processing the user's billing records to form the lia;

tramfierring the iist to the location wtiere it is stored, Le., the switch that wiil conduct the

search and notifying the mobile of any additions and deletions to the l i a In addition, the

authors assumed that for a particuiar user, ali the location areas in the list are under the

control of the wmie switch, but in a reai system, the search list may span multiple

switches. The authors also assumed that aii the cens are identicai, and aii location areas

have the same number of ceiis. In practicai systems, these assumptions are not true; each

system wiii have to be evaiuated independently.

Considering the above assumptions, the authors sbowed thaî the location update t d E c is

reduced on both the radio and fixed networks links, the paging traffic is hcreased on the

radio iink, and the paging t d c remaïns the same in the nxed aetwork when ail of the

location areas are in the same Mobile Switching Center (MSC) coverage area and the list

is maintaineci local to the MSC. These savings are realized at the expense of an increase

in cal1 setup delay for mobile tenninated calls.

In [3], diffkrent pgkg t9chniques namely, simuitaneous and sequential paging are

introduced and arc compared in texms of relative paging delay and paging t d f ï c . The

authors assuwd that the LA is composeci of fixed number of square-sbaped cells,

although in reality, these assumptions are not tnie; each system will have to be evaluated

independently. It is a h assumed that the d-anival rate to each ceil is homogeneous

which is again not true since different cells have different dl arriva1 rates depending on

the users residing in.

One of the main advantages of the analytical k e w o r k presented in this paper is the

closed-fonn expression it provides for the cost of location management in terms of the

dl-arriva1 rate, boundary crossing rate, the size of the LA, the maximum acceptable

average pagiag delay, the total number of cells controlied by the MSC, etc., thereby

allowing valuable insight into the impact of each of these system parameters on the

overall cost of location management.

Y-Bing LUI:

Paper [4] studies a special case of AS called the Two-Location Aigorithm (TLA). It

analyzes the Signalhg System no. 7 (SS7) tranic cost of registration and cail deiivery for

a basic scheme based on IS41 and the TLA An analyticd approach assuming Poisson

cal1 arrivals and general roaming times in the LA was used to determine a probability

a(K), the probability that a mobile user moves across K LAS between two phone calls.

The evaluation of the algonthm uses different LA residence t h e distri'bution for different

termiwis and plots normaiized cost hctions, cornparhg the pmposed scheme with IS-

41 scheme.

The main advantage of this method is the reduction of Location Updates (LUS) whm a

mobile goes back and forth between two LAS. The algorithm shows that TLA can

outperform IS41 if the user mobility is higher than the c d muency or the user tends to

move back to the prevïously visited Location areas. But the performance of the TLA is

significantly lower than IS-41 when the variance of the LA resideace times is smaii.

Dynamic schernes ailow on-line adjustments based on the characteristics of each

individuai MT. For example, when the distance-based l d o n update scheme is used, a

diffèrent distance threshold clai be assigned to each hfï based on its mobility and cal1

mival pattern. However, some of these schemes require Monnation, such as the distance

between cells, tbat is not generally available to the MTs. Besides, the operaiion of

dynamic schemes may require signifiant computing power.

Anna Hac and Xmn Zhon:

In the evaluation of [SI, the metric used is total wst in terms of the subscriber's cali to

mobility ratio (incoming calls to Location @tes). Total cost is the surn of the total

searching and updating costs. The simulation results compare the total cost for the three

algorithms: always update, always search and the proposeci one, for a number of different

cal1 to mobfity ratios.

The proposed algorithm does not define the mabod to gather idonnation regarding the

m e n c y of a MT entering the c d . Another problem is the selection of reporthg ceils.

The problem of selecting reporthg centers is based on the volume of conîrol traftc about

the mobility of users and the fresuency with which they are located. If these rates change

dtamaticaüy, the reporthg centers have to be reseleaed It is suggested that in case of

reselection of reporting centers, a dynamic a i l d o n of the reporting centers is done, but

no mention is made of how to do this dynamic allocation.

The main advantage of this scheme is the reduction of total cost in finding the user and

the reduction in the consumption of the wireless channels The aigorithm to solve the

reporthg centers pmblem is well denwd and has the potential to simultaneously d u c e

the radio link bandwidth usage and fixed network sïgnaiing.

L. R Hu and SSR4ppopotî:

The analysis in [6] depends on the dwell the, definecl as the time the mobile terminal

stays within the LA of a given r e g i d o n level. The system uses multiple registraîion

levels to track the locations of MT. Based on the dweli time of an MT' in the previous LA,

an MT is switched to a suitable level for location management. Mobile terminais tracked

by the proposeci scheme are xen to gmerate signaling trafnc at a very stable rate over a

broad class of temiinal mobility. This feahm prevents the system fiom excessive

signalhg trasfic due to high mobiiity users and c m be w d to set the required long-tenn

totai sipnaüng trafic.

In the proposed scheme, thm are no nxed LA boundanes and, for each LA bouadary

cmssings, the mobile terminai is always plsced at the center of a new LA. Consequently,

three major benefits are &tain&

1. The location-updating iate is greatly nduced because a suitable LA is provideci for

each mobile, and the mobile temiinal is always placed at the center of a new L A

2. The location updating signahg traffic is evenly distributed because mobile terminais

roaming in the system wiil cross the LA boundary randomly at different cells.

3. The zigzag effect (muent updates) is elhinateci. Since the mobile terminai is always

placed at the center of a new LA on each location updating, it is unlikely to cross a LA

boundary shortiy a h an irpdating even ifits path is very inegularguiar

The proposed strategy considers homogeneous systems in temis of LA radius. In general

the ceus may have irregular shapes and different sizes. Extra computational compiexity is

required to calculate the dwell tirne.

Thomas Kunz and Jokn Seouriris:

The proposai in [7] attempts to utilize the mobility bistory of the submiber to

dynamically mate location areas for individual subscribers, and to dynaxnically

determine the most probable paghg a n a The mobility mode1 w d to evaluate the

proposed algorithm is based on activity theory bomwed fiom relattd work in trafnc

engineering and social science, and using raw &ta h m regional planning travel surveys.

in providing the lodo11 management cost savings, the dynamic algorithm requires some

additional logic and memory on the mobile station and network (base station a d o r

switch). In tmns of computation, the proposed algorithm requires the mobile station to

record the average time spent in each ceii, and the number of transitions h m one ceIl to

another- In addition, the comparison process whm entering a new ceil is more involved,

requiriag the cornparison of a ceil identifier against a lin of celi iéentifiers (the personal

location area), as opposed to the cornparison of a Location A m Identifier (LAI) aga* a

broadcast LAI. The numkr of cornparisons however is on the order of ten or twenty.

Another additional cost of the dynamic algorithm is the tmdssion of the usa profile to

the network. Only the information related to pghg needs to be ttansfkrrd This transfer

would genefauy be done during a location update, making use of the existing signalhg

c hannel.

Location Updoting W h Akrnotive Tri1pgers:

One of the advantage of non-LA-oriented methods is that the location updates can be

spread over vimially aii the cells of the network, resuiting in a more eveniy distributed

signaling load as cornpand to LA-oriented proposais, which would tend to cause a higher

(location updating) signaüng load rnainly on the LA borda cells.

Tl'me-Bared:

This strategy is simple and each mobile can update its location according to its local

clock. The advantage of this striategy is that the hquency of executing location update

process can be controllable regardles of movement of each subscriber, and update ma

does not jump compared with other strategies. Its drawback is its resource consumption,

which is user-independent and can be unnecessary if the user does not move for several

hours. A MT that mums to its starting location (the location where it had its last

interaction with the network) or a stationary MT will update its location while the

network aireaày knows this location.

One disadvantage of this strategy is that d e n a MT moves into and out of a particdar

ceil repeatedly (e-g.. a mobile located at the boundary of two ceils), it has to initiate an

update for every M boundaq crossings although no location update is necessary. Extra

logic and memory is required to be aware when the MT cross boundaries between ceiis.

The implementation of the distance-based strategy is more dinicult than the other two

since the mobile need information about the topology of the cellular network to derive the

distance information.

Centraiized Dofabase Architecture:

The centraüzed database structure that records al1 movements of MT in a central database

has a simple algorithm to locate the MT. However, its implementation is hpracticai

because the centraiized dataôase carmot support such a large number of M T s in a globai

system. With this scheme ail usem have to access only one central database in aIi

situations even if both the d e r and the c a k e are in the same location area, and thus it is

impractical to serve al1 users in real time using a single database, and it is impossible to

connect a cal1 in case that problems occur in an HLR Momver, the cost (Le., number of

operations in the daîabase) of an updaîe for a relocation is flxed, and does not depend on

the distance between the previous and cunent locations. For example, a movement within

a city and a movement to a new conrinent are treated the same, yet mmy movements are

likely to take place withh a city, while movements to another continent are rare. Due to

the dominahg disadvantages of cenealiad database architecture, most of today's

proposais are baseci on either the distributed or the hybrid database architemure.

Distributed Database Architecf ute: -- --

In Distributeci Daîabase Architecture, location information of the MTs is distributed

among a large number of location databases, organued as tree structure. The hierarchical

architecture helps to duce the total network signaüng t d 5 c and traveliing distance

when most calls received by the users and most regiçtration area crossings are

geographidly localized However, a large number of location databases have to be

accessed during location registration and cal1 delivery, *ch increases the wmplexity of

the management proceàure. For example, in a distributed algonthrin, ail related layer

nodes have to execute cornplex Iogic depending upon the received message type

whenever an update request or connection request is received. So the main drawbacks of

this architecture are the cost of database qstem acquisition, implementation, and

management. Momver, the performance of this architecture saongly depends on the

design of the tree structure and mobility characteristics of the users.

Jan Jannink, Derek hm, No~oyunaa Sivorkmw, Jennifrr Widom and DonaCd CC-

The analysis in [ I l ] depends on the L o d Cal1 to Mobiiiîy Ratio ('Cm) defined as the

numbei of caüs nom a particular switch to a pariicular subscriber, relative to the number

of moves of the subscriber in a given time period This ratio is computed to decide

whether to replicate the user profile at a set of or not sirh that the benefit of

local lookups at these databases outweighs the update cost due to the user's mobility.

From the simulations it is showed that more than 90% of the calls can be serviced by

local database lookups. The penalty paid for the latency improvement is an increase in

bandwidth requirement, and near doubling of memory requkements and update rates.

One of the desirable feature of 1111 is that instead of assumiag a nonrealistic mobility

model that incompletely characterizes human caüing and mobility penems, the authors

used a realistic call and movement model of the subscnirs to simulate accurately the

performance of the LMTs in a close approximation of a real geographical topology.

The algorithm for selecting databases where profile replicas are most advantageous to be

p l d is well defined. With the advances in fiber optic techwlogy and the dropphg of

storage prices, the flexiility of We-long numbering with fhst lodrups will become very

important.

P. Kkishrta ei al:

In the evaluation of 1141, the metnc used is total cost in texms of the suhcriber's cal1 to

mobiIity ratio. Total cost is the sum of average update cost, average search cost, and the

average search-update CO& The cost of a location @te and search is chamcterized by

the number of messages sent, size of messages and the distauce the messages need to

travel. Simulations were carried out to evaluate the @omurnce of various location

mamgment strategies.

The Logical Network Archi- (LNA) considercd in the proposal is a hicrarchical trec

structure consisting of BSs and MSCs which maintaias the idonnation of the MT

residing undemeath them. The paper does not discuss how to gather information

regarding the mobiity khavior of the users. It is assumeci that, initiaily, the location

information of the MTs is storeci in the corresponding MSCs i.e., each MSC shouid have

the coma location information for al1 the MTs residing in the celis in its subtree. It is

aIso assumeci that the message deIays in case of searcching the MT are negligible since

message delays are s m d l corn@ to the time ôetween cails and moves.

Considering the above assumptions, the authors showed that performing search-updates

significantly reciuced the search and total costs without significantly incteasing the cost of

updates. For the logical nehuork architecture assumed, it is shown that the combination of

L a y Updates (LUS) and Path Compression Updatte (PCU), namely LU-PC perfonns

better than the other strategies for most d-mobÿity patterns.

nie hybrid database structure wnsists of HLRs, whkh store the permanent MT

information within any network and VLRs in charge of roaming MTs in one or more

location areas. This can lower the congestion probability in the HLR somewhat but has

overheads in multiple àatabase operation because the VLR has to obtain Mïs idormation

fiom the old VLR and delete it in the old VLR Also, the access delay of VLR is not

negligible because the number of MT'S repinend in a VLR varies over time and al1

contents in the VLR have to be searcheci in order to query a MT'S infotmation-

Shivrikumru and W&wc

According to the scheme proposed in [15], user profiles are replicated at selected

locations for faster location loolarp. The replication decision is made by a centralized

system that must c o k t the rnobiüty and calling parameters of the whole user population

fiom time to tirne. This may not k feasible in current PCS networks because of the large

number of PCS network providers involved. Besides, generating and distributing the

replication decision for a large user population is a computationally intensive and time-

consuming process thaî may consume a significant amount of network bandwidth.

The algorithm is anaiytically compared to [24] and another similar approach, based on the

network query s k , and the location loolrup delay. An actual mobility mode1 is not used

to obtain any quantitative results, but raîher variables are used to represent the number of

location updates and the number of kcoming calls h m a particular zone, for generic

subscribers.

Chfi-Lin, Grcrpory P.PoUini and R i c k d D. GilCin:

In the evaluaîion of [lq, the metrics used is the radio link costs, nXed network signaling

load, and c d sencp delay. Conventional approaches iike GSM resewe voice tnmks pnor

to knowing whether a caii is successful or not. In Reverse Virtuai Cal1 setup, voice tnmks

are not reserved until the MT is found and willing to accept the call. Alternatively, the

called party may choose to have the c d routed to a voie mailbox or simply retum the

cal1 via a wired phone, if one is nearby. Thus in addition to sahg the umecessary tNnk

allocation, there is a s8ving in signalirig messages. The cail setup delay is shown to

reduced by about 50 percent when using RVC scheme.

The proposed RVC scheme is compared with the GSM scheme and it is shown that the

RVC c d setup delay is l e s than the GSM c d setup delay. Che of the features of the

RVC strategy is that it can fiinction within the existing cellular paging networic like

GSM. The page is sent as usual and may be acknowledged. However the originaîing

switch does not setup the cd, but instead, waits for a cail to amive h m the called party,

and then bridges the two connedon. Only a few new nxed network SS7 signaling

messages are needed to implement this pmtocol, which rrrr mentioned in the algorithm.

Josepk S. M. Ho und Jan E Akyildk

In 1171, the authors intmdiced a Location management scheme baseci on a three-1evel

database architectirn. The analysis depends on the Local Cal1 to Mobility Ratio (LCMR).

The signaling and database access overhead for cal1 delivery can be reduced if a remote

pointer exists at the DR of the calling MT. However, additional processing is required

after each movement to update the remote pointers. Similarly, the signaling and database

access overhead for location registration can be reduced if location change is reported to

the HLR only after inter-DA movements. However, this will incrrsse the database access

overhead for cal1 deüvery, as an additional DR access is necessary to locate a caüed MT.

The paper assumes that the cost for database access a d the cost for transmitting signaling

messages are available. An enhancement to the proposed location management scheme is

introduced which lowm the inter-DA movement probability and thus d t s in

additional reduction in the signahg and Aatahaîe access costs.

One of the features of the proposed algorithm mentioued by the authors is thet it can be

employed with the existing celiuiar system like I S 4 . The fiinctions of the network

elements iike HL& n R etc remain mostiy unchangeci M e the DRs handle additionai

processing. The papa gives a compatison of the IS41 scheme with the proposed one.

Based on the coa parameters considerd in the analysis, it is show tbat the signahg and

database access cost is reduced by as much as 70% and 50% re~pectively, cornpared to

the 1s-41 standard. The steps for implementing the algorithm are weil defineci in the

Pape=-

R Juin and Yi-Bùtg Lin:

In [18], a pointer-forwarding scheme with single HLR is proposed and is compared with

IS-41 scheme. When an incoming c d arrives in a single HLR environment, the

forwarding pointers are traced to fïnd the actual location of the MT. Each tirne a user

moves, the user's HLR mwt initiate updates to all the replicas of the user's profile, and

the network will have to cany the packets generated by the ripdates. Hence, the larger the

number of replicas, the more work perfonned by the HLR and the network. Because of

the heavy signaihg tratnc generated by PCS location tracking, the HLR may becorne a

bottieneck. An additionai consideration is the higher storage -ment of databases in

zones in order to store the replicated pmEiles.

The PFSHLR scheme ù cornpanxi to the IS41 scheme and it is pmved that when the cal1

fkquency is much lowa than the MT move fiequency (LCMR), pointer forwarding may

outperform IS41. When the caii îkquency is higher than the M ï moves fkequency,

pointer forwarding behaves identidly to IS-41.

In 1191 a pointer forwarding nrattgy has been proposed to avoid the expaisive HLR

access each t h e a mobile moves to a new LA. Since no regiseation to the HLR is

perfonned when a user moves to the new locations, the cost of updating multiple HLRs is

eiiminated in PFDHLR nius, the advantage of using distributed HLR for pointer

forwarding is obvious h m the aspect of database delay. However, it is Wcuit to

implement distributed HLRs in 1s-41. For MT registration, it may be required to update

some or aU HLRs. Thus, extra traffic is gewrated for multiple HLR updates.

The PFDHLR has some potential side effects. The length of the folwarding pointer chain

may inmease in a distributed HLR environment. Because of the distributed HLRs in

several regions, the total incoming d i s will be SM by ail HL&. Therefore, the

average cal1 arrivai rate in each distributed HLR is 1M times thai in PFSHLR, where N is

the number of HLRs. The reason why N divides the cail mival rate is due to the

assumption that the incoming calls are unifody shared by distn'buted HLRs. This

de- LCMR and the expected number of forwarding pointers increases significantiy.

Kuen-Lbg Sue piid CliKn-Chao Tse~g:

The analysis in [20] is the extension of the proposal in 1191. Similar to PFDHLR,

OSPFDHLR also incorporates the concept of dktributed HL& with pointer forwarding-

This strategy m p t s to migrate the locating c h a h in a distributed HLRs system when a

mobile issues a registration operation so that the forwarding pointer chah does not

exceed one.

The proposed stmtegy pmvides an upper bound on the location tracking tirne owing to

the fact that the length of any locathg path does not exceed one. Furthermore, obsolete

entries in local databases VLRs can be reclaimed in this strategy.

One disadvantage of the proposed algorithm is the increase in the data structure of each

entxy in K R . This data stn~ctwe depends on the number of distributed HLRs in the

cellular network. The more HL&, the bigger will be the data structure that will increase

the complexity of the system.

Another potential problem is that adjusting the forwarding pointers needs some extra

signaling capacity between VLRs. For a mobile which ofim moves across the LA

boundary, but does not frequently receive calls, wnsiderable sigoaüag capacity will be

wasted.

Kin & le un^ and Yonahm L m

One of the advantages of the proposal in 1211 is that c d setup time and response times

for signaling fiinctions cari be reduced. Due to the local availability of the necessary

customer data, tnuismission cost for signaling messages for calls originating nom the

visiteci country or region, and possibly signaüng resources can k saveci. However these

savings and the reduced load on the HDB have to be considemi together with the COS of

additional transmission and database management in the foreign region. Another fwor

thai can degrade the pclfonnance of the replicaîed design is the query-to-update ratio. If

the ratio is high (Le., the customer informaiion is seldom changed), the overhead in

updating the repli& records d l be minimal. Othewise (e-g., for a mobile customer

moving nom location to location), the upâate overhead can be signincaat

Locatîng mobile objects in a worldwide system requires a Scalable location service. An

object can be a telephone or a notebook cornputer, but also a data object (Web page may

move as its owner changes cornputers), a nle or an electronic document (a sharecl

electronic document may travel between its users). Another example is a mobile agent

that moves through the network in search of specific resources for its owner.

As mentioned earlïer, mobile radio communications raise two major problems. First, we

need to improve the signaling and querying efficiency of the network-side database.

Second, we need to reduce radio intediace signaling in temis of location ripdatiag and

paging. This thesis will focus on the second issue and compare the pedionnance of

several propos& on the basis of total signaling cost, i.e., location updaîing and paging

costs.

Several recent location management stratepies have been cummented upon in this

chapter. They al1 seem to have their own advantages and disaàvantages. Some are

reiatively easy to impiement, some might provide high signaüng savings on the d o

link, and some seem to be interesting h m a theoretidconcepniai point of view. At besf

the proposals above were evaluated based on some version of a random mobility model,

typically one-dimensional. CIearly, such simplifications for as critical a component of

location management as subscriber mobility is not satidactory. A random mobility model

fails to take into account certain aspects of travel such as trip purpose, and so-called

attraction zones, where people spend a large proportion of theu the. Random mobüity

rnodels may have provided a mugh model for certain early users of cellular telephones,

such as travelling salespersom, whose movements were fairly random. However, as

wireless technology increasingiy becornes a customer item, such mobility patterns will no

longer reflect reality. There is a aeed to anaiyze the performance of the proposed

strategies by using a more realistic user mobility behavior model iustead of the random

one.

Mer a carefui review of the above-mentioned schemes, severai proposals have been

selected for cornparison against the general goals of location management The reason for

selecting these proposais is that these strategies have the same goal of reducing the

signaiïng tranic due to location management procedures: location updating and paging.

The selection consists of thor proposais that can minimiie signaiing, both over radio

interface and within the network, to d u c e bandwidth usage and increase capacity with

least computational complexity. The paformance meesiaa that are considered in this

theses are the numba of location update messages, the nuxnber of celis paged, and the

total location management cost One of the desirable f m in the evaluaîion of these

aigorithms is that hstead of assuming a nonrealistic mobiïty model that incompletely

c- human mobility paaera~, realistic movement model of the subscribers is

used to simulaie accurateIy the performance of the locaîïon management techniques in a

close approximation of a reai geographical topology.

The select& location updating and paging algorithms for performance cornparison are as

follows:

+ Reprting Centers Algorithm [5].

Distance-Based Algorithm [9J

F W Locution Area Shtegy (a implemented in Cwent Cellulm Networks) [25].

The algorithm in [4] is the extension of Tabbane's proposal in [1] with a difference that

two locations are considered to track the location of the mobile user as compared to AS

which allows more than two user locations in the profile for each arbitrarydefmed time

period. The locations for the two most reccntly visited LAS are stored in the MT. Same

two LA addresses are also storeci in the HLR in an order depending upon the user's

movement Location update is only performed if the LA address of the new ce11 is not

fomd in the memoxy. ï'his may result in las location updating cost as compareci to the

GSM, especially when the user m o v a back and forth between two LAS. When a phone

cal1 arrives, the two addresses in the )ILR are used to fïnd the a d location of the MT.

I f the MT is located in the first @y, thm the paging cost for =A is the saw as the GSM

algorithm. ûtheLYYise extra penalty incurs in T'LA to locate the MT for the second try.

The proposal in [SI adckses the major poblem of reducing the use of radio fesources

for location updating d paging activitiesy thus miniminng the tratnc on the radio link

which is considered as the most rarce resource. The aigorithm in the paper uses a

partition scheme to optimize the size of the location area domain that mhhkes the total

cost for the entire network rather than for each individual user. A f k a carefiil sdection of

reporting centers (ceils with the lowest fkequency of mobile users), the MT is dowed to

transmit update messages only at these reporthg centers, while restricting every search

for the mobile user to a srnall subset of cells. Wbenever there is a need to establish

communication with a particuiar mobile usery the user is searched for in al1 cells that are

in the vicinity of the reporthg center to which the user fast reported. This may reduce the

signalhg cost in terms of location updating and paging.

Ideaily, the mobility tracking scherne used for each user shouid depend on the user's cal1

to mobility pattern, so the standard approach, in which al1 cells in the location area are

paged when a cali arrives, may be wastefûl of wireless resowces (especially if the user is

not very mobile and gets muent calls of short duration). In order to conserve these

resources, the network must have the capability to seiectively page to a gtoup of celis in

which the probability of fïnding the user is maximum. On the 0th hami, keepïng closer

track of the user's l d o n involves additional expendmires since the MT uses power for

iistening to the kacons broadcast by the radio c b e l (to detect changes in his location)

and for alerting the aetwork of a location change. These ~flections lead us to include the

Distance-Bad Strategy [9] for fiirtber evaluation. By using this strategy the system

knows that the user is within distance D h m the ce11 whae he has last rrported. This

may r e d t in l e s paging signaling in case of a c d mival. Also the user only has to send

a location update signal when he crosses the threshold distance D b m the ce11 where he

iast updated his Location. This wil l resuit in the signaihg reduction for location updating.

The location management stmtegies in [7] and [25] are seiected for cornparison purposes.

The algorithm in [7J is based on a dynamic selection of cells to fom a LA each thne a

user moves to a new ce11 and is clairrieci to be better than the GSM dgorithm. The GSM

approach is the digital cellular standard currently under use in Europe, and is based on a

staîic set of LAS. Due to the diverse nature, both of these algorithms will contribute in the

cornparison of the above mentioned proposais.

Chapter 4

Mobility Models and Experimental Setup

Location management has received a fair amount of attention recently, as higher capacity

cellular sysiems are king developed. As can be seen in the Iieyiew of different Location

management algorithms in Chapter 3, most authors have used simple random mobility

modeis to evaluate the performance of k i r proposais. To reflect the &y to &y

movements of actuai mobile users, a mobility mode1 may be needed which is more

redistic than a random mobility model. This chapter presents a realistic mobility rnodel

designed to simulaîe realistic mobility behavior patterns of the mobile users. A random

mobility model is also presented as most of the previous work is based on simplistic

models that incompletely characterize human mobility pattem. The two mobility models

will be used for the performance evaluation of selected proposais fiom Chapter 3. The

procedures used for computing the optimal parameter values for selected proposais are

also mentioned.

A mobiiity model, in the context of location management, is a model of the daily

movements of mobile subscnbers, or more precisely, the daily movements of registered

mobile stations. Such a model is of paramout importance in mobility management

midies. The number of paghg and location update messages, required for cornparisons of

the efficiency of different location management schemes, depends fiindamentally on wr

mobiiïty patterns. Thm have ken several proposais for location management algonthms

in the ment past mentioned in Chapter 3, to irnprove upon the current methoà of using

statically dehed location anas describeci in Chaptcr 2. In attempting to quantifi. the

performance of their proposais, most authors have used mobility models that are overly

simplified and unreaiistic, completely random, or dependent upon many assumed

%ypicai9 values for key variables.

DiEerent location management pposals nsct differently to the randomness of users

behavior. Random mobility models have been fhquently used in the past due to their

simplicity, and the faft that d y usm of cellular commUILications had typidly been

very mobile subscribers whose behavior could be reiatively weii modeled as random.

With the tremendous p w t h of cellular comrnUILiCations, random mobility modek are no

longer accurate for the majority of subsdbers, whose behavior is more mutine. A

random mobility model would cause very biased resuits for proposais that attempt to

utilize the behavioral aspacts of subscriber mobility, for example, the importance of home

and workplace as trip origins and destinations.

The mobility model that formed the bask of the simulation study is the same as presented

in 17. A brie€ overview of the mobility model is given hen. Interested readers axe

referred to 171 for a detailed description of the mobility model.

The mobility model description is followed by a description of our random mobility

model. As mentioned in the previous chapter, random mobüity models fail to take into

account certain observeci aspect of travel such as trip purpose, and places where people

spend a large proportion of their day, nich as home, office, etc. The selected proposals

will also be simulaiecl mder a random mobility model and a detailed cornparison is done

for the selected proposals under both mobility models. A description of selected

algorithms and theV implementation mder both mobility modeis foilows ne%

The goal of the mobility model is to provide, at the individual subscriber level, a set of

paths traversed on a daily basis. Using this informafion, location management algorithm

can be cornparrd accordhg to the relative number of location updates and paging

messages they generate. The mobility model used here is the activity-ôased mobility

model [q. The input data for this mobility model was derived h m the trip survey

conducted by the Regional Municipality of Waterloo in 1987. The driving parameter in

the model is the wncept of activity, which is equivalent to trip purpose. Each activity has

an associated time of the day, duration, and Iocation. An activity is selected based on the

previous activity and the cumnt time period- Once the next activity is selected, its

drwtion is determined h m chronologicaliy sorted trip nwey records, by calculating the

Merence between the arriva1 time of one trip record, and the deparhm t h e of the

following îrip -rd Finally the location of the activity is selected, based on certain

heuristics and type of activity. Since the current location of the submiber is already

known, once the location for the next activity is selected, the intermediate route (in terms

of cells crossed) is determined h m a geographicai lookup table. The subscnber stays in

the destination celï for the duration of activity, and the quence is repeated. As opposed

to a randorn mobility modei, w h m thae is no concept of subscribers with different

mobility patterns, four différent user groups are de- with different mobiiïty behavior.

As the model will be used to evaluate location management algorithms, a period of

several days will be sirnulated to allow the system to reach steady m e . The finai output

fiorn the model wül therefore be a list of celis traverseâ by an individual subscriber over

a period of several days, together with the amoiint of time spent in each c d .

In a random mobility model, a user moves to a neighboring cell with random and equal

probability. Two -11s are calied neighbo~g ceils if a mobile user c m move h m one of

them to another, without crossing any other c d . As opposed to the redistic mobility

model where four categories of person type were defineci, the analysis presenteû for the

random mobility model in the sequel will refa to a particular user (arbitrarily chosen).

According to the c d layout considered in this study, a ceil can have at the most six

neighboring cells. In a realistic mobility model a number of ceils may be crossed between

the origin and destinaton of a trip; the subscriber will spend some amount of t h e at the

destination, which wili likely be longer than the tirne spent in the intennediate cells. In a

random mobiiity model thm is no concept of destination celi, thus every next

neighboring cell is selected with equai probability. The d d o n for which a user stays in

a celï is selected randomly (ranging fiom O - 8 hours at the most).

A discrete event simulation schedules events in a queue to occur at certain times baseci on

a global clock, and these events are dequeued in chronologieal order and acteci upon

based on the event type. The occurrence of a particular type of event triggers a

corresponding fimctïon. The simulation is starteci with an initial aipgeneratïon event,

whose parameters are enterd by the user. The tripgeneration fûnction creates and queues

a set of cell-change events. A ceii-change function perfonns any location updating

fùnctions that may be triggered when a change of celi occurs. The tripgenemtion

function also mates and queues another tripgeneration ment

Cal1 arrivals are not mdeled using the typid Poisson arrivai proces, since the model is

not very realistic for individu81 subscribers receiving d s . A subscriber is much more

likely to receive a c d at 2 PM than at 2 AM, a fact not accoimted for by a Poisson model.

A dl-arriva1 hct ion generates and queues cal1 arrivais for the next 24 hours based on a

heuristic probability distribution for cal1 arrival tirne. The call-8RivaI fünction also

queues an event that will trigger the generation of the next set of cal1 arrivals.

For the reaiistic mobility model, four independent variables are used as inputs to the

simulation. Person type and work location variability parameterizes the mobility aspects,

while the number of daily cail arrivals aff'éct the location management algorithrns. For

each wmbination of the independent variables, a number of repetitions of the simuiation

are executed, each with a randomly selected set of intemat parameters (such as home

location).

For the random m o b ' i model, as there is no concept of user graups, home cell etc, the

only input is the number of incornkg a i ls . The tripgCIlCrafion event, ceiî-change eveat

and d l - h v a l event are the same for the random mobility model as for the rdistic

mobity model.

The simulation continues nmning mtil the master clock crosses a userdefineci threshold,

nominally set at 15 simulateci days. Outprit daaiIing l-*on apdatt and paging messages

generated by the différent location management algorithms is logged to extemal files,

which are analyzed by separate software.

4.4 Goals und Consttainis of fkc Algorihm

In Chapter 3, diffamt proposais w m compared agaïnst the general goals of location

management. These same goals form the basic requirements for the selection of the

selected algoriîbms. Certain trade-offs are necessary since many of the goals are

contradictory in practice. Priority was given to m h h k b g the bandwidth required for

location updates and paghg. Providing adequate quality of smice in tmns of cal1 setup

delay (due to p@ng delay), as well as preserving battcry Me, were dm given high

priority in the selection procedure. The description of the s e I d algorithms dong with

the e>q>erimental setup of both models for the aigorithms follows.

Anna Huc arid Xhn Z l t o ~

The proposal by Anna Hac [SI is based on minimizing the total signaling cost for the

entire network rather than for each individuai user or wr group. Since each user group

has its own characteristics and mobility patîems, each cell has a diffaent fkquency with

which the mobile users enter that ceIl. The fkquency with which the mobile w r s enter a

cell corresponds to the updating cost for the di. The higher the fkquency, the higher the

updating cost. The problem is how to choose the ce& as reportkg centers to mhhize

the total location management COS, Le., both updating and searching cost The concept of

total location mauagement cost is a way to observe the o v d effects and behavior of

different algorithms and is defïned in detail in the next chapter. Here it can be thought of

as linear combination of the number of location iipdatiag and paging messages. To cope

with the pmblem of reporting centers selection, the foiiowing approach is used.

To calculate the fiequency with whïch the mobile users enter the ce11 in the redistic

mobility mode1 simulations were nui for di f f int sets of input parameters and the output

results h m the simulations were used to evaiuate the movement of simulated subscribers

on a per ce11 basis. The rnovements and messages generated by each subscriber dong

with the path taken were Logged for 15 simulated days. For each combination of the two

independent variables @emn type, fixed work location) that parameteriz the mobility

aspects, one hmdred repetitions were run each with a randomly selected set of i n t d

parameters (initial start time, location of home, work, and school). Output detaihg the

path traversed by the subscribers dong with the fkcpency of subscriber entering in each

ceii is logged to an externa1 me. The fiquenies with which usen enter each ceIl were

added togetheq which gives the total tiequency at which al1 mobile users enter the cell.

The cek with the highest fkquency were sel& as non-reportuig centers by making

use of the reporthg center selection algorithrn mentioncd in [SI.

Simulations were nin with diffêrent values of vicinity Z for différent sets of input

panuneters and the output is logged to an extemal file for total location management con

caicdation. For each set of controlled variables (person type, fked work location,

maximai vicinity size @=3.4,5, f), and number of daily call dvals), ten repetitions

w m run, each with a differetlt set of internai parameters (initial start tirne, location of

home, wock, and school). The number of location updates and pages were tabulated, for

each Metent set of controiied vanables and the total cost was calculateci. From Figure

4.1, it c m be seen that the costs are relaîively independent of Z as diffêrent values of Z

Figure 4.1: Total Lacaîion Mimagement Cost d e r the Redistic MoOiMy Model for

Z = 3,4,5,6,7

give very similar @ormance- Thus the one giving the minimum location management

cost, Z = 5, is selected as the laqest vicinity SUC for final simulations.

In case of out random mobility model, as there is no concept of user groups and

destination tek, the concept of calculating the fkquency of mobile users in the ceiis

ciiffers h m the distic mobility model. As in the realisac mobility model, a user

traversed the shortest path in travelling fiom cell a to cell b and the number of times he

crosses each ceU is counted- In the random mobility model, the destination ceii can only

be one of the ne ighbo~g cells of the cell in which the subscriber cumntiy resides in.

The fhquency with which mobile users enter the -11s depends upon the number of times

the cell is selected as the next cell. Thus for calcuiating the fkequency, one thousand

repetitions were simdated five times. Out of five thousand simulation results, the in-ce11

fkequency was calculated.

After the fkquency calculation, the algorithm in [SI is used again for reporthg center

selection. Simulations were nm for d i n i n t values of vicinity (Z = I , 2,3,4,5,6,7). AArr a

carefiil review of al1 the results, Z = 2 was selected as the maximum vicinity size for the

random mobility model (Figwe 42). The cost difference between realistic and random

mobility model (Figwe 4-2 vs. Figure 4.2) results is due to the fact that unda a d is t ic

mobility model a user has to cross several cells to reach to the destination. Under the

random mobility model, the same ceiis can be reselected each thne as the destination ce11

so the user can keep moving betwan two celis which cm be in the vicinity of the same

reporthg cell.

Figure 4.2: Total Locatkm Mimagement Cost undet the Rudom Mobility M i e 2 for

2 = l,2,3,4,5,6,7

F M Loccrtian Area Sdrofw (a ih@kmetcd in Cment CeUuiar Nè!uorks):

In the Fixed Location Asea strategy [25], a N-cell system is panitioned into static location

areas- The mapping h m ceIl to location area is fixed. Location areas can have different

numbers of cells, dependhg on the number of mobile users and geographicai proxïmity.

A mobile initiates a location update when it moves h m one LA to another. in 171 four

Merent locations area groups were compared using the rdstic mobility model. Afkr a

carefiil review of the redts in [A, the location area mapping givhg the best results is

selected. The selected scheme partitions the 45 radio cells into total of eleven location

areas, with three to five cells in each.

Y-Bing LUI:

The LA mapping for the TLA schmie [4] is the same as that of the fked location area

strategy. TLA is implemmted by modifyiog the nxed location ana strategy. The

modifications were doae in two places. Fkt , one more field is added to the subscriber's

location record in the main database to hold the address of the second location area

Second, a few changes wcn made to the MT record to e x d s e TLA.

Dktance-Based Algorilkm*

In the DistanceBaseci Method [9], a MT @omis a location update when its distance

fkom the cell where it @ o d the last location update exceeds a predefhed value T

(this distance value is referred to as the distance threshold). To select the threshold

distance for the tealistic mobility modei, simulations were run with différent threshold T

values and the output is logged to an extemai file for total cost calculation. For each set of

controlled variables @erson type, nXed work location, tbreshold distance (T =

l.2.3.4.5.8.I O), and number of daily c d arrivais), ten tepetitions were nm, each with a

different set of interrial parameters (initiai start time, location of home, work, and school).

The number of location updates and pages were tabulsted for each set of contrdled

variables. From Figure 4.3, it can be seen thaî both T = 2 and T = 3 have very Nnilar

px50rmance, with T = 3 perforiniag slightly better. So a threshold value of T = 3 is

selected that gives the minimum location management CO&

Figure 4.3: Total Location Mànagement Cost under the ReaIistic Mobility Mode1 for

T = I,î,3,4,5,6,7

For the random mobility modei, fifieen simulations were nm with the différent values of

threshold distance (T = 1.2.3,4,5,8,10) and the total location management cost is

calculated, The resuits show that T = 1 and T = 2 resuits in the minimum values of the

total location management con showing very simiiar results (Figure 4.4). So T = 2 is

selected for final simulations.

Dyriamic Locatbn Management A&oriikrn=

The Dynamic Location Management Algorithm [q atternpts to u t i k the mobility

history of the subscribcr to dynamicaliy create location areas for individuai subsCnbers.

and to dynamidly determine the moa probable p@ng area The system starts with an

empty history record and develops a mobility history as the subscribers traversed baween

ceiis. The mobility history consists of the number of transitions the subscnba has made

Figure 4.4: Total Location Mmiogement Cost under the Random MobiZity Model

for T = 1,2,3,4,5,6,7

fkom ceil to ce& and the average duration of visits to each c d . A set of cells is selected

for the new location ana, S U C ~ that the probab'itty of the subscriber subsequently

roamhg within those cells is sufïïcientiy hia. For an incoming cd, the subset of the

location area where the subscriber is most iïkely to be found is paged first, based on the

subscrïber's average visit duration in each ceil.

An efficient mobiie location tracking sïrategy should minimize the combined cost of

paging and location update. This combined cost depends on a mobile's mobility as well

as its inwrning cail mival rate. Two mobility models, realistic mobility mode1 and

random mobility mcxicl, are prescnted that are used to simulate the mobility patterns of

the mobile users. The nalistic mobility mode1 is implemented to simulate the daiiy

movements of mobile subacribers (in temis of a sequence of radio cells), incorporatïng

reaiistic, hdividuaiized activity patterns and geographid focal points. The model is used

as a tool for cornparison of the selected proposais. A random mobility model is also

implemented as most authors have used some version of a random mobility modei for

performance evaluation of their proposai. Simulations were perfonned to analyze the key

performance pmneters of seiectcd dgoritbms under both moôility mdels. The NO

mobility m&Is wïil be used for the performance evaluation of the selected location

management algorithms.

Chapter 5

Performance Analysis

The selected location management algorithms are compareci in this chapter, primarify in

temis of radio bandwidth efficiency. As discussed in the previous chapters, one of the

most important goals of location management algorithms is efficient utiiization of radio

spectrum, which is a fixed and limîted resource. Maintabhg the number of location

updating and peging messages that m m be transmitted across the radio interface can

satisfy this requirement. Simulations are pafonned to analyze the performance of the

selected location management strategies. Results wii i be obtained for both realistic and

random mobility models. Statisticai analysis is performed to compare the performance of

selected algorithms under botb mobility models. The need for statistical output analysis is

based on the observation that the output data h m the simulation exhibits random

variabiiity when random number generators are used to produce the values of the input

variables; that is, two Merent streams of random numbers will produce two sets of

outputs which (pmbably) wiil ciiffer.

5.1 Description of Data and Procedures

The analysis involved performance evaluation of location management algorithau under

both reaiistic and =dom mobility models. The original output h m the mobility models

provided detaüs about paging and location update messages generated over time by a

91

simulated subscnber, for each select& algorithm. For the d is t ic mobility model, the

movements and messages genciated by each subscriber was logged for 15 simuiated

days an interval assumecl at the outset to be long enough for the model to reach steady

state. For each set of controlied variables (person type, fixed wodc location, and number

of daily call arrivals), thirty repetitions wcrr nin, each with a different set of internai

parameters (initial start tirne, location of home, woik, and schooi). The number of

location updates and pages were tabulateci, per simulated day, for each different algorithm

and for each &fiirent set of oontrolled variables. O v d , there were 120 parameter

combinations (4 person types x 2 fixed work location states x 3 daily call arrival levels x

5 algorithms) with 30 repetitions for each combination, for a total of 3600 individual

mns.

As in the realistic mobility model, the movemems and messages generated by a

subscriber in the random mobility model were also logged for 15 days. Thüty repetitions

were nui for a Merent vaiue of daily calI arrivals and a different initial start time. The

number of location updates and pages were tabulateci, per simulatecl &y, for each

different algorithm and for different cal1 arrivai rates. Overall, there were 15 parameter

combinations (3 daily di arriva1 levels x 5 algorithms) with 30 repetitions for each

combination, for a total of 450 individual mm.

Due to the number of independmt and dependent variables and the wmplexity of the

data, statistid adysis on the data was deliberately kept simple. Various meam,

standard deviations, and COIlfidcnce intervals at a 99% confidence level are calculateci

using MicroJOft Excel. Caiculation of confidence intervals helped evaiuating the

pe~omiance of the sel& algorithms. If the mean cost matrk of one aigorithm is better

than that of others and their respective confidence intervais do not ovalap than, based on

the data at han4 there is a strong statistical evidence that this algorithm is better than the

other. If there is an overiapping of the confidence intemals, then there is no strong

statistlcal evidence that one system design is better than the other a d the two rtlgonthms

show very similar pedomurnce.

5.2 Comparison of Locaion Managemien f-Re fated Signoling

The average number of location update and paging messages generated by the different

algorithms were compared. The total location management cost a rsther abstract but very

signifïcant concepf was also calculateci and used to compare the overail performance of

the algoritbms under both mobility models.

5.2.1 Overd Average Performunce

Location Ujdating:

The graph in Figure ' i l shows the cumulative number of location @te messages for

different algorithm averaged over al1 relevant variables @cm type and nXed work

location) for the realistic mobility model. It shows the overall relationship between

selected algorithms. Tnt reporting center sûategy performed the worse. This is evident

from the fkct that the reporthg centers are fked baseci on the reporthg center selection

Figure 5-1: Global Average N w n k of Location U w e s versus Elapsed Time under

the Realistic Mobility Mo&

algorithm mentioued in Chapter 4, and not created dynamidiy based on the mobility

behavior of the subscribers. According to the network topology used in this study, some

of the reporthg centers have a vicinity size of one, thus generating a lot of update

messages if the subscnbr traverses dong a path containhg these ceiis. The fixed

location area stmtegy better than the reporthg center strategy but worse than

distance-based strategy. As expected, the TLA strategy perfonned better than the fked

location area strategy which shows that the mobile users tend to move back to the

previously visited location area.

The dynamic location area strategy gives the best resuit. The 'leaming curve' associated

with the dynamic algorithm is clearly visible on the graph, As time progresses, the user

profile is able to provide better information for ceU selection. At first the results of the

TLA algorithm w m betkr than the dynamïc algonthm, but the dynamic stratcgy star&

performing betta &et six elapsed days, and the @ormance gap increased as time

Table 5.1 Mer demonstrates the results in Figure 5.1, showing the means, standard

deviations and 99% confidence intervals of al1 the five selemd algoritbms for the total

n u m k of location updates sent under the distic mobility model. It is clear h m the

table that there is stmng statistical evidence that dynamic algonthm is better than the rest

of the dgorithms.

Table 5.1: 99A Conmnce Interval Estimation ofhcation Urnes un&t the Realistic

MobiIity Mo&Z

Reporting Cemter

Tw*hmtion

Fid LA

Dyrrimic Algorithm

DiSena+pI.rA

The graph in Figure 5.2 shows that the two-location algorithm pdormed better than the

dynamic algonthm under the random mobüity model. It was expected, since the

randomness of cells visited does not aliow usefùi user profiles to be wiistru*cd for the

dynamic algorithm. For the two-hation strategy, the next sel& cell can be in the

same location ana as the previous ce& or the addnss of its location arcs is already

Man

138.48

118.76

135.88

100.08

125.45

StdDcv

44.95

3920

3828

26.88

34.45

99% Confidence Inîenrl '

[131.01- 145.951

[Il224 - 125.281 [12931- 1424

[95.61 - 104.551 [1i9.72 - 13 1-18]

present in the main memory as the last witcd LA, thus reducing the number of location

updates.

The reporting center algorithm pedormed the worse again for the same reason as

explained above. The nxcd location area strategy perfomed better under the =dom

mobility model than under the rralistic mobility model. This can be explained by

reasoning M a r to tk tw01Iocatiioa aigorithm case.

Figure 5.2: Global Average Number of Location CIpdms versus EZapsed Time under

the Random Mobility Madei

The number of location @tes gencratcd by every aigorithm under the randorn mobiiity

model are ais0 analyzed statistidy by caicuiating the means, standard deviations and

99% confidence intervals (Table 5-2). The resuits show m n g statisticai evidence that the

two-location aigorithm pedormed extremeiy weii, while the reporting center algorithm

Table 5.2: 99% Confidence lntmul Estimation of Location Upcims under the Radom

Mobility MO&I

The overail average number of cells paged is shown in Figures 5-3, 5-4, 5.5. und 5.6 for

levels of 6 and 12 incoming calls per day, rrspectively under both mobility models.

Under the realïstic mobility model, the resuits d e almoa linearly with the ciiffernit

incoming call levels, indieating that the dynamic paging algorithm performs better

relative to other algorithms regardes of paging load Dining the fïrst few days, while the

user profile is king compiled, the performance of the d y d c algorithm was somewhat

worse than other selected algorithm, as the reporting centa algorithm perfomed the

best,

This gap, however, typically disappeared a h 2 elapsed days after which the

performance of the dynamic algorithm is the bm The distance-based algorithm perfom

the worst for both incoming d l levels. This is evident h m the f e that if the mobile

user is not located in the neighboring ceiis in the first m g try, then extra pcnaiiy has to

be paid by paging ail the cells Mder the threshold distance T = 3.

Figure 5.3: Global Average Nmber of Cells Paged for 6 Imoming Ca& versus

EIapsed Time under the Realistic Mobility Mode1

Figwe 5.4: Global Average Nwnber of Celh Paged for 22 Ihcoming CaUs versur

EIapsed Time under the Realistic Mobiliîy Mo&Z

Figure 5.5: Global Average Number of Cells Pagedfor 6 Incornittg Calls v e r m

Elapsed Time d e r the Rondom Mobilis, Mode1

Under the random mobility mode], the reporting center strategy performs the best and the

two-location algorithm and dynamic algorithms perform the worst. For the dynamic

strategy, it was expected, since the randomness of ceUs visited does not aiiow usefiil user

profiles to be constructed and most of the tirne a large location area (whose maximum

size is bound by the algorithm) is selected as paging area. For the two-location algorithm,

its poor pe&onnance was also expected since if the user is not located in the fint try,

extra penaity incuis to locate the user for the second try, that is, the paging messages are

sent to the second LA in the memory.

Figure 5.6: Global Average Number of Cells Pagedfir 12 Incoming Calls versus

Elapsed Time Mder the R&m Mobility Modd

Despite the poor perfiorrnauce of the reporthg center algorithm with respect to the

number of location upâate messages sent under the random mobility model, its paging

cos is the minimum for both levels of incoming calls. This was somewhat expecteà. as

the number of cens paged in case of an incoming cal1 are amiost two.

The statisticai analysis for the number of ceiis paged for levels of 6 to 12 incoming calls

per &y d e r both mobility moàels is shown in Tables 5.3. 5.4, 5.5 and 5.6. For both

levels of incoming d s under the realistic mobility model, t h e is strong evidence that

the dynamic algorithm performs significantiy better while the distance-based algorithm

performs the worse (Table: 5.3,5.4).

Table 5.3: 99% Confdeence Interval Estimation of Number of CeZls Paged for 6 Incoming

Calk unrier the Redistic MobiZity Mode1

Table 5.4: 99% CoIrfidence Interval Estimahion of Nmber of Cells Pagedfor 12

Incoming Calls d e r the ReaZistic Mobility Mode1

Dynrmie Aigorithm L

D i t a n c ~ ~

Under the random mobility mode1 the statisticai analysis provides strong evidence that

the reporting center algorithm perform better than the other algorithms as its mean

403.9 1

849.75

number of ceUs paged is smaller for both levels of 6 (Toble 5.5) and 12 (Table 5-6)

incoming calls. Since there is overiapping between the confidence intervals of the

91-96

197.48

dynamic algorithm and the WO-location algorith, there is no signiscant diabence

l388.62 - 41 9.21

[8 1 6.92 - 882.581

between the resuIts of these two, but they are clearly the worst performers.

Table 5.5: 999 ConjWonn Inremal Esn'manon of Number of Cells Paged for 6 Ineoming

CalZs under the Random Mobility Mode1

Table 5.6: 99% Confidence Intemal Estimution of Nmber of Celk Paged for 12

hcoming Calls under the Radom Mobility Mode1

5.2.2 Total Locatio~ Managememt Cosl

The dynamic scheme performs best for location upâates and paging under the realistic

mobility model. Under the random mobiity model, the two-location strategy performs

best for location updates, but is nearly worse for pages dong with the dyaamic strategy,

due to trade-off between efficient location updating and p-g, while the reporthg center

strategy performs the best because of smaU paging area sizes. The total location

management cost defined in the Chapter 4 as the lin= combination of the number of

location iipiating end paghg messages, is a way to observe the o v d effects and

behavior of diffaent algorithms. It c m k defined in severai ways, such as the total

number of sigding messages crossing a specific interfkce, or the total size in bytes of al1

exchanged signaling messages. Some authors nmply rrpcsent cost as an abstract

constant- in this anaiysis, an intermediate approach has been taken, which is quantitative,

yet not limiteci to a specific technology. The location management cost is given by:

Nh is the number of location upâate messages generated, Np is the number of ceils paged

as a result of an incoming di, and c is a constant mpresenting the relative wst of updates

to pages. Since a location update is a much more expensive procedure in terms of

signaling t h pages, the two repmentative values of c are taken as 5 and 10. These

values ate somewhat arbitrary, but represent the approximate sUe and number of

signaiing messages required by a Location update amparrd to a paging message.

Signincant ciifferences in the relative cost of different algorithms mise as the number of

incornhg cal1 increases under the realistic mobility model- For relative wst c = 5, and 6

incoming caIls per &y (Figure 57), the distance-based dgorithm, reporting center

algorithm and the fixed location a m aigorithm have v 9 similar performance and incur

the highest costs. This is due to the excessive updatiag and paging costs r e q d by these

D Y -

O 1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5

Dey. Elrpœd

Figure 5.7: GlobaI Totd Location Mimagement Cos? (c = 5) for 6 lncoming Culls versais

Elapsed Time d e r the RealistÏc MobiIity Mo&

The dynamic algorithm outpedorms ail other algorithrns after a brief ' l e h g curve' of

about three elapsed days This was expected since the dynamic algorithm produced the

least location iipdate and paging messages. As the number of incoming cails increases

(Figue 5.8)' the gap between the dynamic algorithm and the other dgorithms increases.

Figure 5.8: Global Total Location Management Cost (c = 5) for 12 Incoming Calls

versur EZapsed Time d e r the Realistic Mobiliw Mode2

For a relatively larger cost of updaîes (c = IO), the worst performers are still the distance-

based, reporting centers and fbced location algorithm (Figures 5.9 ond 5.10) for both 6

and 12 levels of incornhg caiis. This was not surpnsing, since updates are relatively more

expensive, and these algorithms generate by far the largest number of updates. As before,

the two-location aigorithm e o r m s better thsn the other three but worse than the

dynamic algorithm. The two-location algorithm with corzesponding low rates of updates,

starts out the best of ail algorithms, but its large paging cost causes total cost to rise

significantly with a higher level of incoming calls.

The dynamic algorithm again outperforms the other algorithms, after a 'Learning c w e 7 of

two to three &YS. The gap between the total cost of the dynsmic and the other algorithms

is even pater for c = 10, since the updating efficiency of the dynamic algorithm

Figure 5.9: Globd Total Locution Mmgement Cosf (c = l O) for 6 Inconhg CaZZs

versus Elizpseed Time undet the Realistic Mobiliîy Mo&

Figure 5. IO: Global Total Location Mariagement Cost (c = IO) for 22 Incoming Ca&

versus Elapsed T h e un&r the Realistic Mobility Mdel

becomes even more important.

The statistifal analysis of the total location management c ~ a for c = 5 and c = 10, for 6

and 12 incornhg CSUS per day under the redistic mobility mode1 is show in Tables 5.7,

5.8, 5.9 and S. 1 O.

1 M a n I Stdïkv 1 99% Coafïàence Interval 1

Table 5.7: 99% Conjîdence Intewd fitimatzmanon of Tot& Location M i g e m e n t Cost for

c = 5 and 6 Incorning CaiIs under t h Redistic Mobilily Mudei

I M a i 1 Stdïkv 1 9!W6 Confdcciee Interval

Table 5.8: 9909 Confidence Interval Esn'mation of Tot& Location Management Cost for

C Dyaamic Algorithm

DUC.~tze-Bad

91 1.48

1492.85

181.44

23220

188 1 32 - 94 1 -641

11454.25 - 153 1 -451

Table 5.9: 99% C 0 n t . e Interval Estimution of Total Locaiion Management Cosrfor

c = 10 anà 6 Incoming Calk under the Realistic MobiZity M&

Table 5. IO: 9909 Coqfidence Intmai Estimation of Toid Locuiion Munagement Cost for

c = 10 und 22 Incoming CaZh Mder the Realistic Mobility Mo&Z

r

Reporting Ccater

TWO-Lmation

It can be seen that there is stmng statistïcal evidmce îhat the dynamic algorithm @omis

signincantly better than other algorithms while reporthg center, fixai LA and distance-

Man

2 124.98

1932.65

based sttategies perforrn worst for both levels of incoming calls.

Under the random mobility model, the relative performance of al1 algonduns is nearly

StdDev

453-42

369.45

opposite to their relative pedomiance under the realistic mobility model. For relative m s t

99% Coafdcice IntervaJ

c2049.6 - 220036] [la71 23 - 1994.07]

c = S and 6 incoming caLIs per day Figure S.II) , the dynamic algorithm that

outperforrned al1 the other algorithms under the reaiistic mobility model incurs the

highest cost This is due to the excessive paging cost i n c d by this algorith, which is

not offset by its inherently low upâating COS. This is expected, since the dynamic

algorithm rqu ires construction of the user profile that depends on the movement of the

mobile user. But in the random mobility model, the randomness of ceb visited did not

d o w usehi user profiles to be constructeci. The reporthg anter strategy that performed

the worst mder the distic mobilïty mode1 gives the best d t s unda the mndom

mobility model. This resuits h m the relatively low paging cost, and the gap increases as

more incoming calls arrive (Figure 5.12).

Figure 5.1 1: GIobd Total Location Mimagement Cos? (c = 5) for 6 Incoming C d s

versus EZqsed Time Meier the R-m MobiZiîy Model

Figure 5. I2: Global Tord Location Mànagemew Cost (c = 5) for I2 Incoming CalZs

versus Elapsed The under the Random Mobility Model

The performance of the distance-baxd strategy, which is initially not good but better than

the dynamic, the mm-location and the fïxed LA strategies for 6 incoming c d arrivais,

shows quite good resdts for increasing cal1 mivals. This is expected, since it perfoms

better in tmns of paging cost, which fomis an important proportion of the total cost for a

value of 5 for relative cost c. The @ormance of the two-location strategy, *ch was

better than the dyaamic and the fixed location area strategies due to its low location

update rate, reacbes the same as that of the dynamic sttategy as its large paging cost

causes total cos to rise signifïcantiy with a higher Level of inwming caiis.

For relatively more expensive updates (c = IO), the two-location algorithm is the least

expensive algonthm for 6 incoming calls (Figure 5. I3), but is overtaken by the reporthg

center strategy as the nimiber of incoming d s inmeases (Figure 5-24). This is because

the two location algorithm incurs low nites of updates and shows the best d t for l e s

incoming caiis, but its large pagine cost causes total cost to rise significantly with higher

levels of incoming calls.

Figure 5.13: Global Total Location Managernent Cost (c = 10) for 6 Incoming Calls

versus EZapsed The M e r the R&m Mobiiity Mudel

Figure 5.14: Global Total L m o n Munugement Cost (c = IO) for 12 Incoming Calk

versus Elupsed T h e un&r the R d o m Mobilily M&l

The statisticai analysis rcsults for c = 5 and c = 10, and 6 and 12 incorning d s per &y

under the random mobüity mode1 are shown in Tables 5.1 1. 5.12, 5.13 and 5.14. It can be

seen that for c = 5 and both 6 and 12 incoming c d s pet day, there is a strong statistical

evidence that the reporthg center strategy is ktter than the other algorithmî. On the same

statistical grounds it is evident îhaî the dynamic aigorithm is the worst performer under

the random mobiiity mode1 for the levels of 6 and 12 inooming caUs per &y and a

relatively smaii @te cust multiplier (c = 5).

Table 5.11: 99% Cor$dence Intervd Estimation of Tot& Locatzon Mimagement Cost for

c = 5 and 6 Incoming CulZs tmdor the RCUICiOm Mobiliîy Mo&

For a larger relative cost of updates (C = IO), the statistical d y s i s shows that the two-

location algonthm is bater than the rest of algorithm for 6 incornhg calls per &y while

for 12 incoming caiis per day the reporting center strategy proves to be the best.

Table 5-1 2: 99% ConEci;ence Interval Estimation of Total Location Mmgemenf Cost for

c = 5 and 12 Incorning C a k Mdol the Radom Mobüiry Mo&[

Table 5.13.- 9909 Cottjidence Interval Estinmiion of Total Location Mimagement Cost for

t

b

Repartibg Cater , T w o - m t b a

Table 5.14: 99% Confidence Interva2 Esrimution of Totd Location Mimagemeni Cost for

Mau

872.83

765.43

Reporting Cemttr

Two-lmcrtioa

FU^ LA

Dynrmic Algorithm

DUt.a~c-R.uri

StdDcv

5732

4736

Mean

1056.83

1228.8

1247.73

1323.87

1 1345

- 99% CooMemœ Intervil l

[845-88 - 899.781

[743,16 - 787.71

StdDev

53.78

68.57

67.42

94.57

78.6 1

99.k Confdence interval

[103155 - 1082.1 11 I

[11%.56 - 1261 -041

[12 16.03 - 1279,431

[1279.4 - 1 368341 I

[1097.44 - 1 17 1-46]

Chapter 6

Conclusions and Future Work

The increased demand for wireless mobile communicatio11~, coupled with the finite

available spectrum, ha, motivated investigation into altemaiive methods of tracking users

and delivering calls. A mobility management scheme that reduces signalhg aaffic load

and comection setq tirne is a pivotal issue in designing funire Personal Communication

Semce (PCS) networks to sati* Quality of Service requirements and to use network

resources efficiently. Particularly required is scalable mobility management, to meet the

explosive growth in number of users for the cumnt second-generation wireless

communication systems, and to materialize PCS concepts such as terminal, personal, and

service mobility. Many mobility management schemes have been proposed for the

reduction of signaiing aff ic. However, these schemes have not been sunicientiy

compared using a unified performance rncwrr that is fitae of assumptions as to mobility

mode1 or architecture.

6.1 Concfusions

In this thesis, we categorized the various mobility management schemes and cl- the

appropriate domain for each type. Some proposais were selected for fiuiher evduations

that are based on reducing the signaüng traac over the winless networks.

Two mobility models form the basis for comparative performance analysis in this thesis-

The f h t was a realistic, rneasurement-based, place and tirnedependent individuai

rnobility model to simulste the mobility behavior of actuai people. The second was a

random rnobiiity model based on simplified m p t i o n , such as a UZUform distribution of

the direction of travel for each mobile subscriber, as king used in a nmber of proposed

schemes. We analyzed the peiformance of each one of the five selected strategies under

both mobility models, and showed the performance d i f fmnas between the strategies. in

the realistic mobility model, overall, the dynamic algorithm significantly lowers the

location management costs, in terms of signaling messages generated, for al1 parameters

examinecl and the distance-based strategy is the worst one. In the random mobility model,

no single proposal shows consistent superior performance. In general, the reporthg center

strategy seems the best, while the dynamic strategy performed the worst-

From the results it is clear that the rnobility model has a significant impact a d the results

descfibed in various schemes using a random mobiiity model may not seflect the dative

perfomance when deploying schemes in actuai systems-

In this thesis we bave examined the impact of Location update and paging messages on

the radio inte-- These waluations have been made with a fbture wireless network

fkmework in min& ushg d s t i c and random mobility models for user movcments. The

seiection of algonthms was based on th assumptions that the RJource usage on the air

interface is of primary importance. ïhe signaling co~lsumes scarce fixed radio bandwidth,

and thus must be kcpt to a minimum. Anothcr impact of the location updstes k noticed at

the VLR/HLR side, where the transaction rates can be very high and may be a cause of

either saturation or reduction of the processing power dedicated to providing

sophisticated services to the subscrïbers. One area of fiture reseamh is to analyze the

performance of the different proposais undcr both mobility moâels on the basis of

database transactions, the processing overheads associated with them, the amount of

memory required, etc.

For the analysis of the selected proposais it was assumeci that the location update

messages are the major contributor to the total location management cost while the

number of incoming calls are wnsidered fixed for each set of readings. As can be seen in

Chapter 5, d l amvals also influence the performance of the location management

schemes especially when the mbscriber is not very mobile or receives a lot ofcalls during

roaming. Another fuhae set of experiments is to use redistic cal1 arrivd data dong with

reaiistic mobility patterns in order to thoroughly evaluate the xlected algorithm.

The model used here in this thesis tries to incorporate the structure of daily travel patterns

of the mobile users without making use of much simplifkd assumptions. Some of the

assumptions considered in this model are the notion of axed home and school cells. But

in reaiity, these ceiis may be different if the subscrii rnoves to a home (in a different

ceii). The question is that how d d e d do mobility models have to be? How to extend or

modify the mobility model to answer "WHAT-Iï" questions? For example, what wiil be

the effect on the system performance if we add another user group, such as school going

childrni? If we do not want îo make any simpl@ng assunptions, we can a l t d v e l y

collect traces of the actual movement of the mobile users h m a real life system. In this

way, we do not have to caîegorize mobile users into user groups and therefore we avoid

simplifjring assumptions that resuit h m the sornewhat arbitrary nature of such

groupings. However using traces, we have to caiiect data for each user separately and this

will result in higher overheads. It also becomes more difncult to experiment with

alternative scenhos to answer "WHAT-IF" questions if the user mobility is directiy

based on traces.

One area of fùture research is to perfom sensitivity analysis of the selected proposais and

analyze how they behave diaing peak hours. For this we have to make some changes in

the existing reaiistic mobility model to identify and anaiyze the proposal in peak hours

only.

Possible future uses and extensions of the realistic mobility model include modification

of the model to compare the performance of different handoff algorithms. This would

requirp enhancement of the simulation to maintain knowiedge of the duration of calls

(incoming and outgoing) as the subscnber moves h m ceIl to cell. Also, rather than

simulating the movement of individuaï s u b s c r i w the simulator has to deal with the

simultaiieous movement of many subscriôers to create hotspots and capacity congestion.

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