GPSR: Greedy Perimeter Stateless Routing for Wireless Networks

1. GPSR: Greedy Perimeter Stateless Routing for WirelessNetworksBrad Karp; Harvard UniversityH. T. Kung; Harvard University 2008년 6월 3일 전기전자 공학과 컴퓨터 전공 이범재 Korea University Of Technology And Education

2. INTRODUCTION(Geographic Routing: Motivation) • Two dominant factors in the scaling of a routing algorithm are: • The rate of change of the topology. • The number of routers in the routing domain. • Both factors affect the message complexity of DV and LS routing algorithms. • On-demand ad-hoc routing algorithms require state at least proportional to the number of destinations a node forwards packets toward. • GPSR uses geographical routing to achieve scalability, allowing routers to be nearly stateless.

3. INTRODUCTION(Assumptions) • All wireless routers know their own positions (GPS device). • Bidirectional radio reachability - a set of nodes with radios, where all radios have identical, circular radio range. • Topologies where wireless nodes are roughly in a plane. • Packet sources can determine the locations of packet destinations, to mark packets they originate, with their destination’s location. • local registration, lookup service

4. INTRODUCTION(Goal) • The aim for scalability under increasing numbers of nodes in the network, and increasing mobility rate. • Method for Measures of scalability • Routing protocol message cost: How many routing protocol packets does a routing algorithm send? • Application packet delivery success rate: What fraction of applications’ packets are delivered successfully by a routing algorithm? • Per-node state: How much storage does a routing algorithm require at each node?

5. GPSR Algorithm • All nodes maintain a neighbor table, which stores the address and the locations of their single hop radio neighbors. • Upon receiving a greedy-mode packet for forwarding, a node searches it’s neighbor table for a node geographically closest to the destination. • If this neighbor is closer to the destination, the node forwards the packet to that neighbor. • When no neighbor is closer, the node marks the packet into perimeter mode.

6. If greedy fails If greedy works If greedy works If greedy fails GPSR Algorithm • Perimeter forwarding is only intended to recover from a local maximum. Greedy Forwarding Perimeter Forwarding

7. GPSR Algorithm

8. Greedy Forwarding • Packets are marked by the originator with the destination’s location. • A forwarding node can make a locally optimal, greedy choice in choosing a packet’s next hop. • If a node knows its neighbors’ positions, locally optimal next hop is neighbor geographically closest to destination • On a dense network, greedy forwarding approximates to shortest-path routing.

9. Greedy Forwarding D x y

10. Greedy Forwarding D x y

11. Greedy Forwarding D x y

12. Greedy Forwarding D x y

13. Greedy Forwarding D x y

14. Greedy Forwarding • Advantages: • Reliance on knowledge of the forwarding node’s immediate neighbors only. • Negligible state required, dependent on network density, not the total number of destinations in the network. • Consumes considerably lesser bandwidth than • protocols which distribute state globally throughout the routing domain (DV and LS). • Protocols which accumulate state along an entire source route (DSR).

15. Greedy Forwarding Failure • Drawbacks: • There are topologies in which the only route to a destination requires a packet move temporarily farther in geometric distance from the destination.

16. The Right-Hand Rule • Sequence of edges traversed by the right-hand rule is called a perimeter – hence the name perimeter forwarding

17. The Right-Hand Rule • Right-hand rule does not yield a traversal of the perimeter of a closed polygon on all wireless network graphs. • On graphs with edges that cross, the right-hand rule may instead take a degenerate tour of edges that does not trace the boundary of a closed polygon. • Non-planar graphs

18. The Right-Hand Rule z u v • x originates a packet to u • Right-hand rule results in the tour x-u-z-w-u-x w x

19. The Right-Hand Rule z u v • Remove(w,z)from the graph • Right-hand rule results in the tour x-u-z-v-x w x

20. No-Crossing Heuristic • During traversal using right-hand rule, if candidate edge crosses edge taken earlier in traversal, candidate edge is ignored, and the next edge in counterclockwise order is taken. • Problem: blindly removes 2nd edge out of pair of crossing edges, may result in partitioned network z u v w x

21. Alternate Solution • Alternative methods for eliminating crossing links from a network: • Relative Neighborhood Graph. • Gabriel Graph. • Remove edges from the graph that are not part of the RNG or GG - yields a network with no crossing links. • The original graph will not be disconnected as was the case in no-crossing heuristic.

22. Relative Neighborhood Graph • An edge (u,v) exists between vertices u and v if the distance between them, d(u,v), is less than or equal to the distance between every other vertex w, and whichever of u and v is farther from w. • w  u, v: d(u,v)  max[d(u,w),d(v,w)]

23. Relative Neighborhood Graph

24. Gabriel Graph • An edge (u,v) exists between vertices u and v if no other vertex w is present within the circle whose diameter is uv. • w  u, v: d2(u,v) < [d2(u,w) + d2(v,w)]

25. Gabriel Graph

26. Combining Greedy and Planar Perimeters

27. Performance evaluation

28. Performance evaluation

29. Performance evaluation

30. Performance evaluation

31. Performance evaluation

32. Conclusion • Simulations on mobile networks with up to 200 nodes over a full IEEE 802.11 MAC demonstrate these properties: • GPSR consistently delivers upwards of 94% of data packets successfully • it is competitive with DSR in this respect on 50-node networks at all pause times, and increasingly more successful than DSR as the number of nodes increases, as demonstrated on 112-node and 200-node networks • GPSR generates routing protocol traffic in a quantity independent of the length of the routes through the network, and therefore generates a constant, low volume of routing protocol messages as mobility increases, yet doesn’t suffer from decreased robustness in finding routes.

33. Conclusion • GPSR keeps state proportional to the number of its neighbors, while both traffic sources and intermediate DSR routers cache state proportional to the product of the number of routes learned and route length in hops. • GPSR’s benefits all stem from geographic routing’s use of only immediate-neighbor information in forwarding decisions.

34. Q&A