Toward Using Node Mobility to Enhance Greedy Forwarding in Geographic Routing for Mobile Ad Hoc Networks

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Toward Using Node Mobility to Enhance Greedy
Forwarding in Geographic Routing for Mobile Ad
Hoc Networks

• Juzheng (Alex) Li and Sol M. Shatz
• Concurrent Software System Laboratory
• Department of Computer Science
• University of Illinois at Chicago

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Introduction

• Geographic routing, especially the greedy
  forwarding mode in geographic routing is rapidly
  gaining its reputation in the context of wireless
  sensor networks and mobile ad hoc networks.
• Generally, it does not require and store global
  network topology information at each node.
• Resilient to frequent unpredictable topology
  changes

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An example
Source
Source
Destination
Destination
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But

• Greedy forwarding may not always work.
• It may fail simply due to a lack of closer
  neighbors.

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Perimeter routing

• Then the second phase of geographic routing is
  engaged perimeter routing
• Planar graph construction Face routing

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Motivation

• Keep the desired features
• greedy forwarding
• Avoid undesired features
• perimeter routing

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Observation

• To deliver a packet, there are two ways
• Transmission hops (like shown previously)
• Node mobility

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Our approach

• Revisit of greedy forwarding itself
• Progress vs Potential
• Motion Potential
• Motion Potential assisted greedy forwarding

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Our approach

• Revisit of greedy forwarding itself
• Progress vs Potential
• Motion Potential
• Motion Potential assisted greedy forwarding

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Revisit of greedy forwarding
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Our approach

• Revisit of greedy forwarding itself
• Progress vs Potential
• Motion Potential
• Motion Potential assisted greedy forwarding

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Progress vs. Potential

• Progress direct progress
• Progress region
• Potential indirect contribution
• Potential region

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Our approach

• Revisit of greedy forwarding itself
• Progress vs Potential
• Motion Potential
• Motion Potential assisted greedy forwarding

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Motion potential

• The strength to move closer to the destination.

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Motion potential calculation

• Case 1 Node can move into destinations direct
  communication range
• Case 2 Node will not achieve direct
  communication with destination
• (Both based on nodes current motion)

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Motion potential calculation
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Our approach

• Revisit of greedy forwarding itself
• Progress vs Potential
• Motion Potential
• Motion Potential assisted greedy forwarding

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Mobility based Adaptive Greedy Forwarding (MAGF)
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Two cases

• Case 1 Source will keep the packet
• Source node has the highest motion potential
  score
• Case 2 Source will pass the packet to a
  potential node
• Source nodes score is not the highest

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Case 1
Tcache
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Case 2
Tcache T0
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Simulation setup

• Size of environment 2400 2000
• Nodes communication range 250
• GPSR Greedy Perimeter Stateless Routing
  (standard geographic routing)
• MAGF Mobility based adaptive greedy forwarding

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Simulation results

• Delivery rate
• Network density
• Node mobility

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Simulation results

• Average hop count
• Network density
• Node mobility

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Future work

• (1) Delay - Energy tradeoff study
• (2) Sophisticated node mobility predication and
  corresponding motion potential calculation

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Thank you

• Any questions?
• Any advice?