scalable location management for large mobile ad hoc networks
DESCRIPTION
Scalable Location Management for Large Mobile Ad hoc Networks. Sumesh J. Philip. Contents. Wireless Ad hoc networks Issue of Scalability Geographic Routing Scalable Location Update based Routing SLALoM - Scalable Location Management Grid Location Service - PowerPoint PPT PresentationTRANSCRIPT
Scalable Location Management for Large Mobile Ad hoc Networks
Sumesh J. Philip
Contents
Wireless Ad hoc networksIssue of ScalabilityGeographic Routing
Scalable Location Update based RoutingSLALoM - Scalable Location ManagementGrid Location ServiceHierarchical Grid Location ManagementNumerical studyConclusion
Wireless Ad hoc networks
Infrastructure-less networks that can be easily deployedEach wireless host acts as an independent router for relaying packetsNetwork topology changes frequently and unpredictablyKey challenge lies in routing packetsQuite a lot of protocols proposed in literature (table driven/reactive/hybrid)Dynamic source Routing (DSR) works well for small networks
Issue of Scalability
Increasing density increases average node degree, decreases average path length
Routing cost lessAny reasonable scheme might work!
To test scalability, area (playground size) must increase with nodes
Average node degree constantWill present a mobility model that consolidates the above relationship
Traditional Protocols
Table driven incur large overheads due to routing table maintenanceDelayed topology updates can cause loops
On-demand flood the entire network with discovery packetslong latency for discoveryPath maintenance means additional state
No separation between data and controlUltimately, data suffers!!
Any contenders ?
Not many invariants to play with (IP address, local connectivity)Nodes physically located closer likely to be connected by a small number of radio hopsGeolocation techniques can be used to identify a node’s physical positionGeographic forwarding
Packet header contains the destination’s locationIntermediate nodes switch packets based on location
Geographic Forwarding
A
B
CD F
C’s radio range
E
G
A addresses a packet to G’s latitude, longitudeC only needs to know its immediate neighbors to forward packets towards G.Geographic forwarding needs location management!
Desirable Properties ofLocation Management
Spread load evenly over all nodesDegrade gracefully as nodes failQueries for nearby nodes stay localPer-node storage and communication costs grow slowly as the network size grows
Scalable Location based Routing Protocol (SLURP)
Hybrid Protocol that has a deterministic manner of discovering the destination
Topography divided into square grids
Each node (ID) selects a home region using f(ID), and periodically registers with the HR
Nodes that wish to communicate with a node query its HR using f--1(ID)
Use geographic forwarding to send data, once location is known (e.g. MFR)
Example
[12]
[10]
- Home region
- Update/Query
- Location Database
- Data
f(ID) - ID Mod(RT)
ID = 22; RT= 12;HR=22%12 = 10;
DST = 22; RT= 12;
HR=22%12 = 10;
Cost of Location Management
Location RegistrationPeriodicTriggered
Location MaintenanceOperations for database consistency
Location DiscoveryQuery/response
Data Transfer
Mobility Model
Each node moves independently and randomlyDirection , Velocity [v-c, v+c] at tNew direction and velocity at destinationNode degree =
To keep degree constant, A must grow linearly with N
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ScaLAble Location Management (SLALoM)
Define a hierarchy of regions : Order(3), Order(2), Order(1)Each Order(2) region consists of K2 Order(1) regionsEach node assigned a HR in an Order(2) regionTo reduce location update overhead, define far and near HRs; near regions updated frequentlyNodes that wish to communicate with another node query its HR in current Order(2) gridQueries from far HRs find way to near ones for exact location of destination
Grid Ordering in SLALoM
Order-1
Order-2, K = 4
Home region
Terrain divided into Order-1 regions
K2 Order-1 regions combined to form Order-2 regions
Function f maps ID to home region in Order-2 region
Near and Far Home Regions9 home regions around U’s current O-2 are near
Rest are far home regions
Near Home region
Far Home region
Location UpdateIf movement within O-2, update near home regions
Otherwise update all home regions via multicastNear home regions know exact location of U
Far home regions know approximate location (O-2)
Movement
Update
Location Maintenance
On entry into a grid, a node broadcasts its presence
A server node replies with location information that the newly arrived node has to store
Use of timers to avoid a broadcast storm
Mobile Node
Movement
Locationdatabase to store ?
A (A_loc)B (B_loc) …
Location Query
V
W
If U and V in same O-1, V knows U’s location
Otherwise, send a query to U’s closest home region
If far home region, route to nearest “near” home region
Query
Grid Location Service (GLS)
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s is n’s successor in that square. (Successor is the node with “least ID greater than” n )
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sibling level-2squares
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GLS Updates9
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location update
2Invariant (for all levels):For node n in a square, n’s successor in each sibling square “knows” about n.
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query from 23 for 1
GLS Query
Using Multilevel HierarchiesRandom node movements and communication assumptions
Not realistic for all applications for large networksLocalized node movement; network traversals rare
Update cost proportional to mobility
Frequent data connections may occur in a localityMultiple server regions redundantLocal queries stay local
Ideal for a hierarchical set up of node locationsUnfortunately, formation and maintenance of hierarchy is cumbersome
Hierarchical Grid Ordering
(HGRID)Grid hierarchy built from unit grids recursivelyAt each level, one of the four lower level leaders selected as the leader for the next levelGrid ordering arbitrary; alternate orderings possible
Level 0Level I
Level II
Level III
Location UpdateNodes update servers as they cross grid boundariesNumber of updates, and distance traversed by the updates depends upon boundary hierarchyLocalized movement results in low overhead
Update
Broadcast
Location Discovery & Data Transfer
Source sends query to its leader
Query visits leaders until approximate location of destination is found; sends response
Data forwarded to more accurate locations until it reaches the destination
U
V
Query
Response
Data
Performance Study
Application
Transport
Network
LL/MAC
Radio
PHY
CBR
UDP
IP
IEEE802.11
Free SpaceMobility
LocationManagement
GeographicRouting
RandomWaypoint
Glomosim: packet level simulatorSimulator setup
No Noise
Scalability with Mobility (High load)
HGRID performs best, with throughput more than 90% Surprisingly, SLALoMK2 performs better than othersExplained by lower location discovery delay and packet bufferSLURP performs worst
Throughput Discovery Delay
Scalability with Mobility
HGRID performs best overall due to low signaling overheadSLALoM performs worst due to congestion caused by network wide updatesInterestingly, overhead (bytes) more for HGRID than SLURP
Data Delay Control Overhead
Scalability with Network Size
Tradeoff between signaling overhead and throughput/delayHGRID performs best overall
Packets delivered Data Delay
Scalability with Network Size
Overhead (bytes) highest for SLALoM; maintenance of large databases increases overall overhead of HGRIDStorage cost grows slightly with network size for HGRID
Control Overhead Database Size
SummaryIssue of scalability in mobile ad hoc routing
Topology updates congest the networkDiscovery, maintenance cause unnecessary flood
Geographic routing is a potential candidateLocalized and guaranteed
Need scalable location management schemesGrid based protocols (Flat vs. Hierarchical)SLURP, SLALoM, GLS, HGRID
Relative scalability of LM protocols dependant on location update, maintenance and discoveryPerformance studies show HGRID scales well with network size, mobility