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GPSR: Greedy Perimeter Stateless Routing for Wireless Networks

EECS 600 Advanced Network Research, Spring 2005. GPSR: Greedy Perimeter Stateless Routing for Wireless Networks. Shudong Jin February 14, 2005. Recall Last Lecture. Dynamic Source Routing Who gives the path? How to obtain a path? What is the routing metric?

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GPSR: Greedy Perimeter Stateless Routing for Wireless Networks

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  1. EECS 600 Advanced Network Research, Spring 2005 GPSR: Greedy Perimeter Stateless Routing for Wireless Networks Shudong Jin February 14, 2005

  2. Recall Last Lecture • Dynamic Source Routing • Who gives the path? • How to obtain a path? • What is the routing metric? • What information is maintained? • Different from Internet routing, but are there any similarities? EECS 600 Advanced Network Research, Spring 2005

  3. This Lecture: Another Approach • Geographical Routing • Who gives the path? • Routing is done locally by individual routers (hop-by-hop) • How to obtain a path? • Decided at the time of routing, no pre-computed full path • What is the routing metric? • Distance as the routing metric • What information is maintained? • A little local connectivity (and location) information is maintained by each router EECS 600 Advanced Network Research, Spring 2005

  4. GPSR: Greedy Perimeter Stateless Routing • Novel routing protocol for wireless datagram networks that uses the positions of routers and the destination to make packet forwarding decisions. • Greedy forwarding used wherever possible and decisions made using only information about the router’s immediate neighbors. • Perimeter forwarding used where Greedy forwarding not possible i.e. algorithm recovers by routing around the perimeter of the region. • Stateless in that a router keeps state only about local topology, hence scales better as the number of destinations increases. EECS 600 Advanced Network Research, Spring 2005

  5. Greedy Forwarding • Assumed: Packets are marked by the originator with their destination’s location. • A forwarding node can make a locally optimal, greedy choice in choosing a packet’s next hop. • Most of the times the locally optimal choice is the neighbor closest to the packet’s destination. (how locally?) • The ideal case: The packet is successfully forwarded using closer geographic hops to reach the destination. EECS 600 Advanced Network Research, Spring 2005

  6. Greedy forwarding example EECS 600 Advanced Network Research, Spring 2005

  7. How to Know the Positions? • Periodically each node transmits a beacon to the broadcast MAC address, containing its identifier (e.g. IP address ) and position. • X and Y co-ordinates are encoded by two 4-byte quantities. • Mean Beacon Transmission interval is uniformly distributed. 0.5B ~ 1.5B • Upon not receiving a beacon for longer than the time out interval = 4.5B, a GPSR router assumes that either the neighbor has failed or has moved out; the GPSR router deletes that entry from its table. EECS 600 Advanced Network Research, Spring 2005

  8. More Optimizations on Beaconing • Handling mobility • Choice of beaconing interval to keep node’s neighbor tables current depend on the mobility in the network and range of node’s radios. • Reducing overhead • Beaconing generates proactive traffic. To avoid this additional cost, GPSR piggybacks the local sending node's position on all data packets it forwards. Thus all packets serve as beacons. • Q: How to enforce random beacon interval, then? EECS 600 Advanced Network Research, Spring 2005

  9. Greedy Forwarding May Fail • The Greedy forwarding algorithm might fail in circumstances where the only route to a destination requires a packet to move temporarily away from the destination. • An example from the paper • More knowledge on topology help? EECS 600 Advanced Network Research, Spring 2005

  10. Perimeters • When Greedy Forwarding fails, how can we get out of the situation? • Right-hand rule to route around voids EECS 600 Advanced Network Research, Spring 2005

  11. Perimeter Forwarding • Perimeter forwarding makes use of Planarized graphs which are graphs in which there are no crossing edges. • Why need the no-crossing heuristics? Give an example • Two algorithms: RNG (Relative Neighborhood Graph) and GG (Gabriel Graph) EECS 600 Advanced Network Research, Spring 2005

  12. RNG (Relative Neighborhood Graph) EECS 600 Advanced Network Research, Spring 2005

  13. GG (Gabriel Graph) EECS 600 Advanced Network Research, Spring 2005

  14. Planarized Graphs: Example Full graph, the GG subset, the RNG subset. EECS 600 Advanced Network Research, Spring 2005

  15. GPSR • This algorithm combines greedy forwarding on the full network graph and perimeter forwarding on the planarized graph. • State information: All nodes maintain neighbor tables which store addresses of all radio-hop neighbors. • Packet header fields • GPSR packet headers include a field which indicates whether the packet is currently in greedy mode or perimeter mode. • All data packets are marked originally as greedy mode. • Only the packet’s source sets the destination field. EECS 600 Advanced Network Research, Spring 2005

  16. GPSR Operations • Upon receiving a greedy-mode packet • the node forwards it to the geographically closest neighbor if there is one. • When no neighbor is closer, the node marks the packet to the perimeter mode. GPSR also records in the packet, the location Lp, the site where greedy forwarding failed. • These perimeter mode packets are forwarded using Planar Graphs. • Upon receiving a perimeter mode packet. • Forward the packet using a planar graph traversal. GPSR also compares the location Lp with the forwarding node’s location. It then returns the packet to greedy mode if the distance from the forwarding node to D is less than that from Lp to D. • Perimeter forwarding is only intended to recover from local maximum. EECS 600 Advanced Network Research, Spring 2005

  17. Simulation Results and Evaluation • Packet delivery ratio • Routing protocol overhead • Path length • Effect of network diameter (size) • Number of states per router EECS 600 Advanced Network Research, Spring 2005

  18. More discussions EECS 600 Advanced Network Research, Spring 2005

  19. GPSR Example EECS 600 Advanced Network Research, Spring 2005

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