SGPSA Hybrid of Topology and Location Based Protocol for Ad hoc Networks

Jingyi YuComputer Graphics Group

Existing Routing Protocols for MANET

• Topology-Oriented– Distance Vector

• DSDV• AODV• TORA• DSR

– Hierarchical • HSR• Landmark

• Location Oriented– Flooding

• LAR• DREAM

– Hierarchical• GLS• SGPS

Analysis of Topology Based Protocol• DSDV (Destination-Sequenced DV)

• Modified Distance Vector• Use sequence numbers to

differentiate freshness(even and odd)

• Loop free• Fail to converge as node mobility

increases

• AODV (Ad hoc On-demand DV)• Combination of DSDV and DSR• Route Discovery from DSR• Sequence number from DSDV• Reverse Route and Forward

Route (avoid source routing)

• DSR (Dynamic Source Routing)• Aggressive caching• Reduce routing overhead when

flooding• Packets are forwarded according to

“source route”

• TORA (Temporally-order Routing Algorithm)

• Link reversal(Query/Update)• Flow of traffic, network tube• Need routing update delivered by

“temporal order”

Performance Analysis of Topology Oriented Protocols

• DSDV– Converge slowly

• TORA– Implemented on IMEP

• AODV– High delivery rate

• DSR– High delivery rate

This simulation is done for 50 nodes, 1500m x 300mEach node remains stationary for pause time seconds beforesending packets.

Performance Analysis of Topology Oriented Protocols (cont.)

• DSDV– Almost constant overhead

• TORA– Huge routing overhead– Why? Reliable IMEP

• AODV– Large routing overhead

• DSR– Low routing overhead

Location Oriented Routing

• Flooding Based– LAR

• Route discovery by flooding

• Request zone, cache previous position/speed

– DREAM • Periodical flood location

update• The further, the less

frequent update

• Hierarchical– GLS

• Geographical hierarchy• Geographical forwarding• Location servers• Forward pointer

– SGPS• Handle problems when

GPS fails• How to choose more

location servers

GLS Routing Pipeline• Why location servers?

– If every node knows any other node’s position, it can just send packets through geographic forwarding.Problem: Too much location update flooding through the networkSolution: Hierarchical approach, keep a limited amount of location servers

– If we have stationary leaders, those “unfortunate” will be the bottleneck and die out fasterSolution: Each node is some other nodes’ location server

Establish a space hierarchy

Recruiting location servers

Route discovery: Location query

Location responseGet Dest’s location

Route packets to Dest using Geographic

forwarding

Geographical Hierarchy

0000 0010

0001 0011

00 01

10 11

• Global Partitioning• 4 order-n squares form an order-(n+1) square• Each node easily maps its ID to HID• Can extend to module M space partition

• ID Space• Each node has a unique ID (IP to ID, etc)• Positive integer• “Closer” relation

Recruiting Location Servers (Location Update)

• “Closer” RelationA node Y is closer to X than a node Z to X if and only if one of the following is satisfied:

1. Yid < Zid < Xid 2. Yid > Xid and Zid < Xid 3. Z id > Yid >Xid

• Recruiting Location Servers– For each level of grid, a node chooses three nodes closest to its ID as

its location servers.– Keep a table of location servers’ HID– How to choose? Implicit recruiting, i.e., sending location update to each

level

Recruiting Location ServersAn Example

Packets Routing between Two Nodes• Location Query

– A sends a request to the least node greater than or equal to B for which A has location information and so on until the request reaches B

– B responds to A using geographic forwarding– At most N steps if A and B share some order-N square

• Bootstrapping–How does A recruit its location servers?

•A sends its location updates to an order-n square•The first node L picks up the update and begins a location query for A•Assumption: before a location update reaches an order-n square, all nodes have recruited their location servers of order-(n-1) square

–Geographical forwarding•A simple two hop distance vector protocol•Each node periodically broadcasts a list of all neighbors it can reach in one hop•Each entry of neighbor expires in a fixed time and is no longer broadcasted as neighbors, but can still be used. Why? (think of 802.11)

• HELLO messages are not unusual to get lost• Unicast is acknowledged, i.e., invalid entry will be removed due a forwarding packet failure

Proof of Correctness and Efficiency (by induction)

Claim: In n or fewer location query steps, a query reaches the node with the lowest ID closest to the destination in the order-n square containing the source.Suppose the destination is ID 0 and the query starts at X and the node with lowest ID (closest to 0) in order-n square is Y.

Base case:order-1 square. If X = Y, then with 0 step, query reaches Y1. If X != Y, then Y is the lowest node X can route. Otherwise if X can route some other node Y1 lower than Y outside its order-1 square, Y1 would have chosen Y rather than X as its location server.

Inductive step: order-(n+1) square. We want to show if the query is at node X with the lowest ID in its order-n square, then X will route the query to the node Y with the lowest ID in its order-(n+1) square in zero or one step.If X has the lowest node ID in order-(n+1) square, then the claim is trivially true.If X has not, then X will know Y’s location and will not know any node whose ID is lower than Y.

i) X will know Y’s location, since X has the lowest node ID in order-n square, Y must have selected X as its location server at X’s order-n square.

ii) X will not know the location of any node lower than Y outside of its order-(n+1) square since any such node would have chosen Y as its location server in X’s order-(n+1) square.

Thus the lowest node X can location is Y and the query can be forwarded there in one location query step.

Routing Using Location Servers

Problems with GLS• Flooding vs. Location Servers

– Flooding: • Efficient routing• Too much routing overhead

– Location Server:• Fixed amount of location updates• Scale well when nodes are

uniformed distributed• Not adaptive to node density

– Solution: • Balancing between flooding and

location update• Adaptive sub-division• Recruit more than one location

servers in each sibling grid Correct?

• What if location query fails– Forwarding pointer– On leaving an order-1 grid, each node

leaves a forwarding pointer in it indicating that it has moved to another grid

• What if GPS fails– A node can no longer know its position

and hence cannot send location update.Solution: Tunneling through its neighbors

Dynamic Hierarchy for GLS• Problems of naïve solution to

recruit more location servers– Increase routing overhead– Will not improve performance,

since each query will still pick the smallest ID node

• Dynamic Hierarchy– Dynamic space partition– Difficulty: hard to synchronize the

network

22 21 20

12 11 10

02 01 00

An example of a 3x3 grid

An Example of Dynamic Hierarchy

• Each node estimates the number of nodes in its order-1 square• If one detects the square is overwhelmed, it broadcasts to its neighbors SUB_DIVIDE• The next location update will use the new sub-division level to recruit location servers• It also indicates the subdivision level to all its location servers to keep the location servers updated. HID should be sub-division compatible

Bottleneck

Sub_div

Loc_update

SGPS and Tunneling

A B

1. GPS_FAIL Broadcast to all neighbors

2. ACK_OK

4. Forward new location and ID

3. Grant

•Tunneling•Three-way handshaking protocol•On detecting its GPS failure, each node broadcasts “recruiting tunnel server”•Those 1 ring neighbors who have GPS then reply ACK_OK•The GPS-failure node then chooses one of them as its tunnel server•It then update its location as the tunnel server location to its location servers

Simulation Results

Simulation Scenario

• 802.11 radio bandwidth 2Mbps• Distance threshold 200M• No node is a source in more than one connection• No node is a destination in more than 3 connections• Each connection sends 4 128byte packets per second for 20 seconds• Moving speed 10m/s

GLS vs. DSR

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Location Query Failure

Broken links Congestion

Path Length Analysis

• 300 nodes with speed 10m/s • Query travels about 6 hops more than the geographic forwarding

• A tradeoff between routing efficiency and routing overhead

Avery Query Length vs. Response Length

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Routing Overhead Analysis

DSR• route request• route reply• cached reply

GLS• HELLO• Location Update• Location Query• Location Response

GLS vs. DSR

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2x2 GLS

DSR

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Congestion

Not much increase, since almost half of the protocol packets are HELLO

Conclusion and Future work• Compare Topology-oriented and Location-oriented MANET routing

– DSR is the best of non-hierarchical topology routing– Unfair hierarchical routing is not desirable– Flooding based GPS routing incurs large routing overhead– Location server based routing maintains the fairness and avoid location

flooding. But GLS does not support adaptive hierarchy and does not know how to handle GPS failure

• SUB_DIVISION scheme to solve adaptive hierarchy– Implementation of GLS with 2x2 and 3x3 partition shows promising result– Need a consistent hierarchy ID for fine and coarse grid– Need aggregation-behavior scenario

• TUNNELING to solve GPS failure• Acknowledgement: Special thanks to Jingyang, Robert and Hari.