Scalable Location Management for
Large Mobile Ad hoc Networks
Sumesh J. Philip

Wireless Ad hoc networks
Issue of Scalability
Geographic Routing
Scalable Location Update based Routing
SLALoM - Scalable Location Management
Grid Location Service
Hierarchical Grid Location Management
Numerical study
Conclusion

Infrastructure-less networks that can be easily deployed
Each wireless host acts as an independent router for relaying packets
Network topology changes frequently and unpredictably
Key challenge lies in routing packets
Quite a lot of protocols proposed in literature
(table driven/reactive/hybrid)
Dynamic source Routing (DSR) works well for small networks

Increasing density increases average node degree, decreases average path length
Routing cost less
Any reasonable scheme might work!
To test scalability, area (playground size) must increase with nodes
Average node degree constant
Will present a mobility model that consolidates the above relationship

Table driven incur large overheads due to routing table maintenance
Delayed topology updates can cause loops
On-demand flood the entire network with discovery packets long latency for discovery
Path maintenance means additional state
No separation between data and control
Ultimately, data suffers!!

Not many invariants to play with (IP address, local connectivity)
Nodes physically located closer likely to be connected by a small number of radio hops
Geolocation techniques can be used to identify a node’s physical position
Geographic forwarding
Packet header contains the destination’s location
Intermediate nodes switch packets based on location

C’s radio range
A
C
D
F
G
B
E
A addresses a packet to G’s latitude, longitude
C only needs to know its immediate neighbors to forward packets towards G.
Geographic forwarding needs location management!

Desirable Properties of
Location Management
Spread load evenly over all nodes
Degrade gracefully as nodes fail
Queries for nearby nodes stay local
Per-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)

[12] ID = 22; R
T
= 12;
HR=22%12 = 10 ;
[10]
- Home region
- Update/Query
- Data
- Location
Database f(ID) - ID Mod(R
T
)
DST = 22;
R
T
= 12;
HR=22%12 = 10 ;

Location Registration
Periodic
Triggered
Location Maintenance
Operations for database consistency
Location Discovery
Query/response
Data Transfer

Each node moves independently and randomly
 v-c , v+c ] at t
New direction and velocity at destination
Node degree =
 r t N
A
2
To keep degree constant, A must grow linearly with N

  rate of region crossing b
 broadcast cost u
 number of hops v

velocity of node r t

transmiss ion range
2 R
 side of region a
 area of region
 
2

 v
2 RCos
 d


 v
4 R
Location U pdate cost ( c u
)
 
( b
 u ) / sec b

1



 a r t
2



z
 most forward progress n
 average node degree
  mean inter node distance

A z

Area of excluded

Average nodes in region a region
G

N
 d

R

Number of regions
G

R
N
 c u
 
( b
 u )
 
( b
 d z
)
 v
R
( R
2 
R

O ( v N )
N

) f z
( z )

2
 r t
2  z
2
1
 e 2 n z
 
0 r t zf z
( z ) dz e
 
A z

On region crossing
Inform previous region of departure
Inform new region of arrival
Update from any node in new region c m
 
( 2 b
 
); 1
   

 v
4 R
( 2 ( 1


 a
 r t
2
Maintenanc

 )
 
) e Overhead

O ( v )
N

Total number of nodes
 
Average number of nodes per region

Cost of Locating
Send a Location query to Home region c l

2 u

2 d z

O ( N )
Total Overhead = Sum of all overheads for all nodes c
 c u
 c m
 c l

Nv N

Nv

N

O ( vN N ) / sec
N

Define a hierarchy of regions : Order(3), Order(2),
Order(1)
Each Order(2) region consists of K 2 Order(1) regions
Each node assigned a HR in an Order(2) region
To reduce location update overhead, define far and near HRs ; near regions updated frequently
Nodes that wish to communicate with another node query its HR in current Order(2) grid
Queries from far HRs find way to location of destination near ones for exact

Terrain divided into Order-1 regions
K 2 Order-1 regions combined to form Order-2 regions
Function f maps ID to home region in Order-2 region
Order-1
Home region
Order-2, K = 4

9 home regions around U’s current O-2 are near
Rest are far home regions
Near Home region
Far Home region

If movement within O-2, update near home regions
Otherwise update all home regions via multicast
Near home regions know exact location of U
Far home regions know approximate location (O-2)
Movement
Update

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
A (A_loc)
B (B_loc)
…
Mobile Node
Location database to store ?
Movement

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
V
Query
W

sibling level-0 squares sibling level-1 squares s n s s s s s s sibling level-2 squares s s s is n ’s successor in that square.
(Successor is the node with “least ID greater than” n )

2
...
1
23, 2
6
23
6
...
26
...
11
9
9
11, 2 3
...
16
2
...
29
...
17 ...
25
7
...
5
...
21
...
4
...
8
...
19
...
Invariant (for all levels):
For node n in a square, n ’s successor in each sibling square “knows” about n.
location table content location update

2
...
1
23, 2
6
23
6
...
26
11
9
9
11, 2
...
3
...
16
2
...
29
...
17 ...
25
7
...
5
...
21
...
4
...
8
...
19
...
location table content query from 23 for 1

Random node movements and communication assumptions
Not realistic for all applications for large networks
Localized node movement; network traversals rare
Update cost proportional to mobility
Frequent data connections may occur in a locality
Multiple server regions redundant
Local queries stay local
Ideal for a hierarchical set up of node locations
Unfortunately, formation and maintenance of hierarchy is cumbersome

Grid hierarchy built from unit grids recursively
At each level , one of the four lower level leaders selected as the leader for the next level
Grid ordering arbitrary; alternate orderings possible
Level II
Level 0
Level III
Level I

Nodes update servers as they cross grid boundaries
Number of updates, and distance traversed by the updates depends upon boundary hierarchy
Localized movement results in low overhead
Broadcast
Update

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
Query
Response
Data V
U

Glomosim: packet level simulator
Simulator setup
Random
Waypoint
Mobility
Application
Transport
Network
LL/MAC
Radio
PHY
CBR
UDP
IP
IEEE802.11
No Noise
Free Space
Location
Management
Geographic
Routing

Throughput Discovery Delay
HGRID performs best, with throughput more than 90%
Surprisingly, SLALoM
K2 performs better than others
Explained by lower location discovery delay and packet buffer
SLURP performs worst

Data Delay Control Overhead
HGRID performs best overall due to low signaling overhead
SLALoM performs worst due to congestion caused by network wide updates
Interestingly, overhead (bytes) more for HGRID than
SLURP

Packets delivered Data Delay
Tradeoff between signaling overhead and throughput/delay
HGRID performs best overall

Control Overhead
Database Size
Overhead (bytes) highest for SLALoM; maintenance of large databases increases overall overhead of HGRID
Storage cost grows slightly with network size for HGRID

Issue of scalability in mobile ad hoc routing
Topology updates congest the network
Discovery, maintenance cause unnecessary flood
Geographic routing is a potential candidate
Localized and guaranteed
Need scalable location management schemes
Grid based protocols (Flat vs. Hierarchical)
SLURP, SLALoM, GLS, HGRID
Relative scalability of LM protocols dependant on location update, maintenance and discovery
Performance studies show HGRID scales well with network size, mobility