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Ontology-based context management agent for vertical handoff use Fuzzy logic decision in heterogeneous network

Nguyen Thi Thanh Huong, GITS, Waseda University, Japan

Email: [email protected] Mitsuji,

GITS, Waseda University, Japan

Abstract

In recent years we’ve seen an increase in number of mobile

devices and mobile applications, running over different

types of networks (e.g., WLAN, 3G, 4G,, UMTS, WiMAX…)

that enable any-where, any-time kind of applications. The

user is getting flooded with these applications and the

information they provide. Seamless mobility intersystem

roaming across heterogeneous wireless access networks

will be one of the main features in the management

architecture of future generation mobile networks. In this

paper we propose an ontology-based context management

agent policy to manage access networks and handover

fuzzy logic decision algorithm for future heterogeneous

wireless networks..

Keyword: Ontology, heterogeneous networks, fuzzy logic

1. Introduction

Mobile communications and wireless networks are

developing at an astounding speed, with evidences of

significant growth in the areas of mobile subscribers and

terminals, mobile and wireless access networks, and

mobile services and applications. The present time is just

right to start the research of next generation mobile

communications because of:

Possibility, according to the historical indication of a

generation revolution once a decade, and now we are near

the end of 3G standardization phase and the beginning of

4G deployment.

Necessity, according to 3G goals, 3G is necessary but not

sufficient to the mobile communication strategy, in which

many problems are only partly solved and there are still

many problems left to be solved in the next generation

(NGN).

The trends in next generation networks can be structured

into different levels [1]:

solutions: such as electronic business and mobile business;

communities, entertainment; collaborative work in virtual

organizations mobile support; knowledge management;

advanced process control support;

contents and services: important trends in this area

include location dependent services, personalization of

content and services, and a change in quality of services:

from the provision of information to user interaction and to

legally relevant transactions.

devices: new devices are characterized by becoming

smaller and more powerful, supporting the trend of

unification of telephony, computer and entertainment,

multi-modal and multi-media access.

networks: the different kinds of networks are converging:

telecommunication, Internet, TV and local area networks;

the user is always connected to services and contents.

Some important requirements for the next generation

network, autonomy capabilities of the entity, and

generating performance measure both for the of networks

Proceedings of the First International Conferenceon Complex, Intelligent and Software Intensive Systems (CISIS'07)0-7695-2823-6/07 $20.00 © 2007

need to be satisfied: provide users with added-value and to

help them navigate through the massive content and

service offerings., exploit the potential of multimedia,

large bandwidth access to content and services. The more

different networks carry personal information, the more

security issues become critical, as network profiles are

becoming more complex and dynamic. New ways of

designing and managing for network management systems

supporting scalability through self-organization and

hand-over between different networks are needed; Our

promise of based context management agent in

heterogeneous network is to be a key vehicle for:

-achieving enriched information of users and providers.

-enabling more intelligence in service provision and

network management and dealing with the enlarging

amount of information and functions, and allowing

self-organizing networks.

The paper is organized as following: in section 2 we

describe the model of context management agent

architecture; in 3, an ontology-based management profiles

in future networks; session 4, introduce vertical handover

use fuzzy logic decision based on ontology profiles; in 5,

performance evaluation, concludes and future works.

2. Context management agent architecture model. Context management agent that we proposed defines,

retrieves, updates and stores file information, manages

generic resources that are not tailored to specific protocol

layers, defines additional labels that characterize the

optimization of handover process.

The Profile Management (PrM): aggregates profile

information related to the connectivity, access and the

upper layer. This includes the profiles of users exploiting

the autonomous entity, the application and service profiles,

QoS profiles of specific reconfiguration session, the

profiles of discovered radio access technology, as well as

the device profiles

in term of processing, memory, energy, software

capabilities [2].

The Resource Management (RsM): manages generic

resources that are not associated with a specific RAN and

devices. For example, the RsM executes the bandwidth

allocation requested from the radio module due to ongoing

resource reservation and locates elementary spectrum

resource.

The Performance of Management (PeM): monitors

resources that are provisioned by the RsM.

The Reconfiguration and Autonomy Classmaking (RAC):

evaluates all profile data handled by the PrM and generates

a dynamic label that describes the capabilities of the entity

in terms of supposed reconfiguration actions level. Fig1.

present architecture of context management agent.

Context information may be classified based on their

frequency of changes and based on their placement. In the

former case, it is either static or dynamic, it can be hosted

either on the terminal side or on the network side. The

contexts that do not change very often are static context

information, whereas those that change quite frequently

and may loose accuracy over time are dynamic context

information.

SGSN

SGSN GGSN

3G Core network

Context management

IP core

PrM RsM PeM

RAC

3G 4G

DVB-HWLAN

WAG

RNC

APC

WiMAX

APC

RANs

RAC: Reconfigurability Autonomy Classmaking

PrM: Profile Management

RsM: Resource Management

PeM: Performance Management

RANs: Radio Access networks

Figure 1. Context management Architecture for heterogeneous network

Agent

Core node


3. Ontology-based context management The management of the knowledge of user context aspects

such as the user identity, its activity and the respective

location and time is one of the main issues of

“context-aware Systems”. More recently, the exchange of

context information has been proposed for the proactive

configuration of IP-based access network elements in order

to improve the handover process of the mobile terminal

(MT). In the IETF, the Stemm K.H has proposed a Context

Transfer Protocol that exchange context information such

as security, policy, QoS, header compression, and AAA

information to preserve the session flow in intra-domain

handover [3]. One of the main issues related to context

management systems is the representation of context

information.

Some markup languages and information models have

been developed and proposed as basis for context

information representation:

• Extensible Makeup Language (XML) is a meta-language

for describing markup languages that provides a facility to

define tags and the structural relationships between them.

• Resource Description Framework - Schema (RDF-S) is

used to improve RDF semantics. It is useful for the

statement of classes, hierarchy of classes and properties,

and to indicate which classes and properties are expected

to be used together for declaring “vocabularies” (i.e., the

sets of property-types defined by a particular community).

• The Composite Capability/Preference Profiles (CC/PP)

uses RDF for limited representation of context

information. It defines a “two-level” hierarchy of

components and attribute/value pairs for describing a

profile of device capabilities and user preferences that can

be used to guide the adaptation of content presented to that

device. RDF and CC/PP information model are serialized

in XML.

• General User Profile (GUP) is currently defined by the

3GPP. GUP is a collection of user related data which

affects the way in which an individual user experiences

services. It is serialized in XML schema. It has a more

complex but flexible structure.

After the reviewing of different languages and information

models we consider that NGN network model information

is suitable for representing our “mobile customer” concept,

because its structure provides a better organization for

introducing complex relationships between elements than

the RDF CC/PP approach. However, it lacks of the

benefits provided by other languages focused on

semantics, such as the Web Ontology Language (OWL, not

an acronym). OWL is the ontology language proposed by

the W3C. Briefly, ontology is the formal definition of a set

of concepts that describe a domain, their taxonomy,

interrelation and the rules that govern these concepts.

OWL expands RDF-S information model adding more

vocabulary along with a formal semantics for describing

properties and classes. Among other features, OWL is a

standard ontology language used in several different areas.

Fig 2. describes a network ontology model.

The based context management agent will have many

parameters with which to make a vertical handover

decision, such parameters should include:

• Signal Strength Measurements

• Bit Error Rates

• Perceived QoS and the QoS requirements current

application

• Network Coverage

• Cost.

• Battery Power requirements to implement the handover -

powering up new interface

• User Preference - user wants to be connected to the

cheapest network available regardless of offered QoS


4. Inter system vertical handover decision use Fuzzy logic In contrast to horizontal handover, vertical handover [3],

which occurs between different overlaying access

networks in a heterogeneous network, has a higher layer

of complexity. The time allowed to process an inter-system

handover request is inherently much longer as the mobile

terminal can maintain connectivity to many overlaying

networks, each offering varying QoS to the end user. The

optimal time to initiate the inter-system handover involves

the processing of many parameters. Choosing the correct

time to handover reduces subsequent handovers, improves

QoS, and limits the signaling and rerouting of data

inherent in handover

process [4]. The parameters we propose to use in the

intersystem handover decision-making process include

network conditions, mobile node conditions, and user

preferences, as well as the capabilities of the various

networks in the vicinity of the user. Such as received

signal strength (RSS), carrier to interference ratio (CIR),

bit error rate (BER), block error rate (BLER), power

budgets, mobile speed, and distance from the serving base

station. In order to avoid continuous handover between

two points of attachment, known as the ping-pong effect,

hysteresis margins, dwell timers, and averaging windows

are also used logic to process these parameters and arrive

at a decision whether to handover to another available

logic to process these [5]

class

Wireless network class

LAN

class Bluetooth class

UMTS classGPRS class

GSM

class WLAN

class IEEE80211。

。a

classPacket switched class

WAN

class Parameters class

Parameters classParameters class

Parameters

BER QoS BLER Cost BER QoS BER

class PAN

class

Wire network

class

Network class

Location class

Identifier

class

Operator class

QoS property

class

Capacity

Ran

ge

Dom

ain

Dom

ain

subclass subclass

subclass

class

Circuit switched

subclass subclass subclass subclass

subclass subclass

subclass subclass

Figure 2. A network ontology model

RSS


In this work we are investigating the use of fuzzy

parameters and arrive at a decision whether to handover to

another available network or to remain with the current

access network expecting the current QoS level to improve

and thus avoid unnecessary handovers. Fig 3. describes

fuzzy logic decision based on ontology context

management agent. The handover parameters are applied

to the fuzzifier [6], where they are mapped into fuzzy sets.

The fuzzy sets indicate the “goodness” of each parameter,

e.g. Low, Medium or High, each with a value between 0-1.

These are passed to the fuzzy inference engine where a set

of fuzzy rules is applied to determine if an inter-system

handover should occur at this time.

There are two possible outcomes: handover or no

handover. Example fuzzy rules for both handover and no

handover conclusions are given below.

IF (FDR = Medium) AND (NHO = Low) AND

(TAT = Medium) AND (COST = Low) THEN HO

IF (FDR = Medium) AND (NHO = High) AND

(TAT = Low) AND (COST = High) THEN NOHO

where,

FDR = Frame Drop Rate

NHO = Number of Handovers already executed for

this session

TAT = Time QoS has been above threshold

HO = Handover. NOHO= No Handover

5. Performance evaluation In this paper we will present preliminarily result from the

network access and fuzzy logic handover algorithm. We

perform scenarios in which 100 users are uniformly

throughout the network and focus on the TAT, FDR

parameters to decision handover. These performance

metrics include Probability Distribution Function (PDF) of

them. We assume that the TAT threshold is 0.2s and FDR

hysteresis is 1% in this scenarios. A fuzzy logic rule base

is created based on the known sensitivity parameter. Each

of the input fuzzy variables is assigned to one of the three

fuzzy sets, ”High”, “Medium” and “Low”. The sensitivity

of the input fuzzy variable to the output of the system can

be controlled by changing the universe of discourse.

When an MT is connected to a Base Station (BS), the

parameters from the BS, and the number of calls in the BS

are stored in agent profiles, and these stored values are

used to derive PDF function, and traffic respectively. The

average number of handovers are also stored. The PDF of

parameters can imply the call drop probability, call quality,

and potential uplink transmit power requirements. The

“High” range values indicate that the call drop probability

will be low, the call quality will be good, and the MT can

transmit comparatively less power.

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

10 20 30 40 50 60 70 80 90 100

Users

Pro

bab

ility

Dis

trib

ution

Fun

ctio

n (P

DF)

"High" range "Medium" range "Low" range

Ontology provider

Learn

Use Ontology

Use logic

Probabilistic reasoning

Use analogic

Fuzzy logicDecision

Perform context reasoning

Context management

agent

Figure 3. Fuzzy logic decision based on context management agent Figure 4. Probability Distribution Function of TAT and FDR


The PDF can give an idea of traffic balancing (or new call

or handover blocking probability). The “Low” value

implies a high probability of successful network access

since more handover calls requests can be entertained by

the network. A lower number of handover indicates a

lower switching load and a shorter delay in the processing

of a handover.

6. Conclusion and future works In this paper, a vertical handoff decision use Fuzzy logic

based on ontology context management agent has been

presented. The model that takes into account context

information from difference networks should be suitable

for vertical HO decision making process in heterogeneous

networks environment. The model is fully flexible and

dependent on the number of chosen objectives that will

determine the dimension of the pairwise comparison

parameters for objectives, as well as the number of these

parameter for networks in terms of required each objective.

In future research, we intend to develop an efficient

algorithm for vertical HO decision and to extend the

algorithm further taking into account user location,

movement, velocity and coverage information based on

agent profiles.

References [1] Nikolas, Oliver Hooland, “Evolution of reconfiguration

Management” (Report technical), August 2005. pp. 25-50

[2] T. L. Saaty, “How to make a decision: The Analytic

Hierarchy Process”, European Journal of Operational Research,

1990 Vol. 48

[3] M. Stemm, R. H. Katz, “Vertical Handoffs in Wireless

Overlay Networks”, ACM Journal on Mobile Networks and

Applications, Vol. 3, Issue 4, pp. 335-350.

[4] K. Pahlavan, et al., “Handoff in Hybrid Mobile Data

Networks”, IEEE Personal Communications, April 2000, Vol. 7,

Issue 2,

[5] P. Chan et al., “Mobility Management in corporating Fuzzy

Logic for a Heterogeneous IP Environment”, IEEE

Communications Magazine, Dec.2001, Vol. 39, Issue 12,

[6] H. J. Wang, R. H. Katz, J. Giese, “Policy-Enabled Handoffs

across Heterogeneous Wireless Networks”, Proc. of the 2nd IEEE

Workshop on Mobile Computing Systems and Applications

(WMCSA ‘99), 25-26 Feb. 1999,


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