GPSR: Greedy Perimeter Stateless Routing for Wireless Networks pps

GPSR: Greedy Perimeter Stateless Routing for Wireless Networks B.. Motivation ❒ A sensor net consists of hundreds or thousands of nodes ❍ Scalability is the issue ❍ Existing ad hoc net

GPSR: Greedy Perimeter Stateless

Routing for Wireless Networks

B Karp, H T Kung

Borrowed some slides from Richard Yang’s

Motivation

❒ A sensor net consists of hundreds or thousands of

nodes

❍ Scalability is the issue

❍ Existing ad hoc net protocols, e.g., DSR, AODV, ZRP,

require nodes to cache e2e route information

❍ Dynamic topology changes

❍ Mobility

❒ Reduce caching overhead

❍ Hierarchical routing is usually based on well defined, rarely

changing administrative boundaries

❍ Geographic routing

• Use location for routing

Scalability metrics

❒ Routing protocol msg cost

❍ How many control packets sent?

❒ Per node state

❍ How much storage per node is required?

❒ E2E packet delivery success rate

Assumptions

❒ Every node knows its location

❍ Positioning devices like GPS

❍ Localization

❒ A source can get the location of the destination

Geographic Routing: Greedy Routing

Greedy Forwarding does NOT always work

❒ If the network is dense enough that each interior node has a

neighbor in every 2 Π /3 angular sector, GF will always succeed

GF fails

Dealing with Void: Right-Hand Rule

❒ Apply the right-hand rule to traverse the edges of a void

❍ Pick the next anticlockwise edge

❍ Traditionally used to get out of a maze

Right Hand Rule on Convex Subdivision

For convex subdivision, right hand rule is equivalent to

traversing the face with the crossing edges removed.

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Right-Hand Rule Does Not Work with

Remove Crossing Edge

Make the graph planar

Remove (w,z) from the graph

Right-hand rule results in the

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Make a Graph Planar

 Convert a connectivity graph to planar non-crossing graph by

removing “bad” edges

❍ Ensure the original graph will not be disconnected

❍ Two types of planar graphs:

• Relative Neighborhood Graph (RNG)

• Gabriel Graph (GG)

Relative Neighborhood Graph

❒ Connection uv can exist if

∀ w ≠ u , v , d ( u , v ) < max[ d ( u , w ), d ( v , w )] not empty 

remove uv

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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 )]

Not empty 

remove uv

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Connectedness of RNG Graph

❒ Key observation

❍ Any edge on the minimum

spanning tree of the original

graph is not removed

❍ Proof by contradiction: Assume

(u,v) is such an edge but removed in RNG

w

• 200 nodes

• randomly placed on a 2000 x 2000 meter region

Examples

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Greedy Perimeter Stateless Routing (GPSR)

❒ Maintenance

❍ all nodes maintain a single-hop neighbor table

❍ Use RNG or GG to make the graph planar

if (have left local maxima) mode = greedy;

else (right-hand rule);

}

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Implementation Issues

❒ Graph planarization

❍ RNG & GG planarization depend on having the current location info

of a node’s neighbors

❍ Mobility may cause problems

❍ Re-planarize when a node enters or leaves the radio range

• What if a node only moves in the radio range?

• To avoid this problem, the graph should be re-planarize for every beacon msg

❍ Also, assumes a circular radio transmission model

❍ In general, it could be harder & more expensive than it sounds

Performance evaluation

❒ Simulation in ns-2

❒ Baseline: DSR (Dynamic Source Routing

❒ Random waypoint model

❍ A node chooses a destination uniformly at random

❍ Choose velocity uniformly at random in the configurable range –

simulated max velocity 20m/s

❍ A node pauses after arriving at a waypoint – 300, 600 & 900 pause times

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❒ 50, 112 & 200 nodes

❍ 22 sending nodes & 30 flows

❍ About 20 neighbors for each node – very dense

❍ CBR (2Kbps)

❒ Nominal radio range: 250m (802.11 WaveLan radio)

❒ Each simulation takes 900 seconds

❒ Take an average of the six different randomly generated

motion patterns

Packet Delivery Success Rate

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Routing Protocol Overhead

Related Work

❒ Geographic and Energy Aware Routing (GEAR), UCLA Tech

Report, 2000

❍ Consider remaining energy in addition to geographic location to

avoid quickly draining energy of the node closest to the

destination

❒ Geographic probabilistic routing, International workshop on

wireless ad-hoc networks, 2005

❍ Determine the packet forwarding probability to each neighbor

based on its location, residual energy, and link reliability

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❒ Beacon vector routing, NSDI 2005

❍ Beacons know their locations

❍ Forward a packet towards the beacon

❒ A Scalable Location Service for Geographic Ad Hoc

Routing, MobiCom ’00

❍ Distributed location service

❒ Landmark routing

❍ Paul F Tsuchiya Landmark routing: Architecture ,

algorithms and issues Technical Report MTR-87W00174,

MITRE Corporation, September 1987.

❍ Classic work with many follow-ups

Questions?