SGPS A Hybrid of Topology and Location Based Protocol for Ad hoc Networks Jingyi Yu Computer Graphics Group

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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”

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SGPS A Hybrid of Topology and Location Based Protocol for Ad hoc Networks Jingyi Yu Computer 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 300m Each node remains stationary for pause time seconds before sending 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 nodes position, it can just send packets through geographic forwarding. Problem: Too much location update flooding through the network Solution: Hierarchical approach, keep a limited amount of location servers If we have stationary leaders, those unfortunate will be the bottleneck and die out faster Solution: Each node is some other nodes location server Establish a space hierarchy Recruiting location servers Route discovery: Location query Location response Get Dests location Route packets to Dest using Geographic forwarding Geographical Hierarchy 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 Relation A node Y is closer to X than a node Z to X if and only if one of the following is satisfied: 1.Y id < Z id < X id 2.Y id > X id and Z id < X id 3.Z id > Y id >X id 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 Servers An 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 ) 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 Ys location and will not know any node whose ID is lower than Y. i) X will know Ys location, since X has the lowest node ID in order-n square, Y must have selected X as its location server at Xs 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 Xs 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 nave 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 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 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 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 Routing Overhead Analysis DSR route request route reply cached reply GLS HELLO Location Update Location Query Location Response 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.