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GPSR Greedy Perimeter Stateless Routing

GPSR Greedy Perimeter Stateless Routing. Jennifer Ogunlowo Sarah El-Helw. Background and Motivation. Routing algorithms & Scalability are essential for a rapidly changing network topology. Informing the entire network of current state is costly and isn’t efficient.

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GPSR Greedy Perimeter Stateless Routing

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  1. GPSRGreedy Perimeter Stateless Routing Jennifer Ogunlowo Sarah El-Helw

  2. Background and Motivation • Routing algorithms & Scalability are essential for a rapidly changing network topology. • Informing the entire network of current state is costly and isn’t efficient. • Nodes need a more efficient way to determine locations • Quick changes in topology for mobile networks.

  3. Introduction • Geography assures scalability via geographic routing. • Greedy Perimeter Stateless Routing (GPSR) is motivated by geography. • GPSR measures scalability by evaluating: • Cost to route of each message • Delivery success rate. • Per-node state.

  4. GPSR Algorithms There are two GPSR Algorithms: • Greedy Forwarding • Used when nodes are within radio range of one another. • Preferable method of forwarding • Shortcoming when there’s a void (an area with no nodes in radio range). • Perimeter Forwarding • Used when greedy forwarding fails (void case) • Returns to greedy forwarding once possible.

  5. GPSR Algorithms • Greedy Forwarding • Destination locations marked by originator. • Forwarding node greedily forwards packet to geographically closest neighbor. • Based on nodes’ knowledge of optimal next hop. • Process repeats until destination is reached. • Beaconing is used to realize neighbors positions.

  6. Greedy Forwarding Destination C B No A

  7. Greedy Forwarding Shortcoming Destination • Route to destination may not have any nodes in radio range close to destination • Perimeter forwarding solves this problem VOID

  8. Perimeter Forwarding Destination • Navigate around perimeter using Right-Hand Rule. • Right-Hand Rule: Traverse edges in counter-clockwise order: x-w-v-D-z-y-x • Returns to greedy mode when location is closer than where greedy failed. z v VOID y w x

  9. Simulations • Compare GPSR with DSR performance: • Simulation in ns-2 environment. • Network of 50 nodes. • Nodes follow random waypoint model. • Pause times of 0, 30, 60, and 120 seconds. • Each source annotates packets it originates with destinations’ positions

  10. Results: Packet Delivery Success Rate • At all pause times, GPSR delivers greater fraction of packets than DSR. • Increase in B, beaconing interval, results in slightly reduced delivery success rate.

  11. Results: Routing Protocol Overhead • GPSR has constant overhead as mobility increases (pro-active). • GPSR offers greater savings in routing protocol overhead.

  12. Results : Path Length • GPSR delivers 97% of its packets along optimal-length paths vs. 84.9% for DSR.

  13. Related Work • Greedy forwarding + flooding search when greedy fails. • LAR (Location Aided Routing), an optimization to DSR. • GLS, a scalable and robust location database that store nodes’ locations.

  14. Critique • Approach used to evaluate path length (GPSR). • Solution: Simulate over much sparser networks to evaluate path lengths under perimeter forwarding.

  15. Summary and Conclusions • GPSR achieves • Small per-node routing state. • Small routing protocol message complexity • Robust packet delivery on densely deployed mobile networks. • GPSR benefits from Geographic routing info for forwarding decisions.

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