EILEEN BALCI

GPSR: Greedy Perimeter Stateless Routing for

Wireless Networks

About GPSR

GPSR allows nodes to figure out who its closest neighbors are (using beacons) that are also close to the final destination the information is supposed to travel to

To calculate a path, GPSR uses a greedy forwarding algorithm that will send the information to the final destination using the most efficient path possible. If the greedy forwarding fails, perimeter forwarding will be used which routes around the perimeter of the region.

About the Greedy Forwarding Algorithm

Assuming the wireless routers [nodes] know their own locations the Greedy forwarding algorithm will try to find the closest router which is also the closest to the final destination

Greedy Forwarding Algorithm Benefits

A node just has to remember the location of neighbors with in one-hop

Routing decisions can be dynamically made

Greedy Forwarding Algorithm Drawback

If the network is dense enough that each interior node has a neighbor in every 2/3 angular sector, Greedy Forwarding will always succeed. However, the greedy forwarding algorithm can fail:

Greedy Forwarding fails

Perimeter Forwarding Algorithm Benefits

When the Greedy Forwarding algorithm fails, the Perimeter Forwarding algorithm will be used

Apply the right-hand rule to traverse the edges of the void and find a path using the topology’s perimeter

Perimeter Forwarding Algorithm Drawback

The Perimeter Forwarding Algorithm uses a longer path to the destination so the perimeter forwarding algorithm less efficient and cannot be used alone

Greedy Perimeter Stateless Routing - GPSR

Putting Greedy Forwarding and Perimeter Forwarding together makes the final GPSR which will use the necessary algorithm(s) to find the best path in a given topology

Greedy Forwarding Perimeter Forwarding

greedy fails

have left local maxima

greedy works greedy fails

GPSR

The GPSR is a responsive and efficient routing protocol for mobile, wireless networks. GPSR can be applied to Sensor networks, Rooftop networks, Vehicular networks and ad-hoc networks.

Credits

www.cs.binghamton.edu/~kang/teaching/cs580s/gpsr.ppt

http://www.eecs.harvard.edu/~htk/publication/2000-mobi-karp-kung.pdf

http://www.icir.org/bkarp/gpsr/gpsr.html