Gpsr greedy perimeter stateless routing for wireless networks
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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

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GPSR: Greedy Perimeter Stateless Routing for Wireless Networks

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Gpsr greedy perimeter stateless routing for wireless networks

GPSR: Greedy Perimeter Stateless Routing for Wireless Networks

B. Karp, H. T. KungBorrowed some slides from Richard Yang’s


Motivation

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

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

Assumptions

  • Every node knows its location

    • Positioning devices like GPS

    • Localization

  • A source can get the location of the destination

  • 802.11 MAC

  • Link bidirectionality


Geographic routing greedy routing

Closest to D

A

Geographic Routing: Greedy Routing

S

D

  • Find neighbors who are the closer to the destination

  • Forward the packet to the neighbor closest to the destination


Benefits of gf

Benefits of GF

  • A node only needs to remember the location info of one-hop neighbors

  • Routing decisions can be dynamically made


Greedy forwarding does not always work

Greedy Forwarding does NOT always work

  • If the network is dense enough that each interior node has a neighbor in every 2/3 angular sector, GF will always succeed

GF fails


Gpsr greedy perimeter stateless routing for wireless networks

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

Right Hand Rule on Convex Subdivision

For convex subdivision, right hand rule is equivalent to

traversing the face with the crossing edges removed.


Gpsr greedy perimeter stateless routing for wireless networks

Right-Hand Rule Does Not Work with Cross Edges

z

u

D

  • x originates a packet to u

  • Right-hand rule results in the tour x-u-z-w-u-x

w

x


Gpsr greedy perimeter stateless routing for wireless networks

Remove Crossing Edge

z

u

D

  • Make the graph planar

  • Remove(w,z)from the graph

  • Right-hand rule results in the tour x-u-z-v-x

w

x


Make a graph planar

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)


Gpsr greedy perimeter stateless routing for wireless networks

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


Gpsr greedy perimeter stateless routing for wireless networks

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


Properties of gg and rng

Properties of GG and RNG

RNG

  • RNG is a sub-graph of GG

    • Because RNG removes more edges

  • If the original graph isconnected, RNG is also connected

GG


Connectedness of rng graph

w

Connectedness of RNG Graph

  • Key observation

    • Any edge on the minimumspanning tree of the originalgraph is not removed

    • Proof by contradiction: Assume (u,v) is such an edge but removed in RNG

u

v


Examples

Examples

Full graph

GG subset

RNG subset

  • 200 nodes

  • randomly placed on a 2000 x 2000 meter region

  • radio range of 250 m

  • Bonus: remove redundant, competing path  less collision


G reedy perimeter stateless routing gpsr

Greedy Perimeter Stateless Routing (GPSR)

  • Maintenance

    • all nodes maintain a single-hop neighbor table

    • Use RNG or GG to make the graph planar

  • At source:

    • mode = greedy

  • Intermediate node:

    • if (mode == greedy) {

      greedy forwarding;

      if (fail) mode = perimeter;

      }

      if (mode == perimeter) {

      if (have left local maxima) mode = greedy;

      else (right-hand rule);

      }


Gpsr greedy perimeter stateless routing for wireless networks

greedy fails

GPSR

Greedy Forwarding

Perimeter Forwarding

have left local maxima

greedy works

greedy fails


Implementation issues

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

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


Gpsr greedy perimeter stateless routing for wireless networks

  • 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

Packet Delivery Success Rate


Routing protocol overhead

Routing Protocol Overhead


Related work

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


Gpsr greedy perimeter stateless routing for wireless networks

  • 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

Questions?


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