Min Power Routing in Wireless Networks

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Min Power Routing in Wireless Networks
CS215 Project Report

• Hai Jiang and Zhijun Huang
• March 22, 2001

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Outline

• Introduction
• Previous Work
• Problem Formulation
• Modified Bellman-Ford Algorithm
• Simulation Results
• Conclusion

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Introduction

• Why Min Power in Wireless Network?
• 1. Limited Energy Battery Operated Network
• 2. Interference Reduction and Spectrum Reuse
• How to minimize power consumption?
• 1. Physical Level
• Low-power CPU/Display
• High-capacity Battery
• gt Little Room for further reduction
• 2. Higher Level Power-aware protocols
• MAC Layer
• Network Layer

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Previous Work

• Singh and Raghavendra (98)
• 1/Eremain reflect nodes reluctance to
  forward packets
• Non-localized Dijkstras Algorithm
  Shortest Weighted Path
• Rodoplu and Meng (98)
• Power consumption u(d) d4 ? 2? 108
• Non-localized Bellman-Ford Algorithm
  Shortest Path
• Gomez etc (99)
• Power cost function Pi f(Bi)
• Heizelman and Chandrakasan (00)
• Radio Model Etx (k, d) Eelec k Eamp
  k d2
• Hierarchical Clustering

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Existing Problem

• Network with minhop algorithm
• Critical Node, N6, expends
  power faster
• gt die first
• Problem how to balance power consumption?
• How to consider hop-count constraint?

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Radio Model

• Transceiver/Receiver Circuity
• Eelec 50nJ/bit
• Transmit Amplifier
• Eamp 100pJ/bit/m2
• Transmit
• Etx (k, d) Eelec k Eamp k d2
• Receive
• Erx (k) Eelec k

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Problem Formulation

• Each Node Remaining Energy Ei
• Each Edge Transmission Energy Pi
• Object
• For each path, Min
• such that, Ei gt Emin and Hop-count lt M
• gt
• Min , such that
  Hop-count lt M

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Modified Bellman-Ford Algorithm
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Modified Bellman-Ford Algorithm
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(No Transcript)
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Simulation Settings

• Method
• Simulator written in C
• Algorithms Min-hop
• Min-power w/ Hop
  Constraint
• Min-power w/o Hop
  Constraint
• Parameters
• RadioRange 100 m
• Network Size 600 m x 600 m
• Node Number 100 - 200
• Max Hop 5, 10, 20, No Constraint
• Time Steps 2000 rounds

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Min-power prolongs network lifetime!
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Network Density increase gt Min-power is more
effective
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Critical nodes in Minhop die fast gt Minhop is
the worst !
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Network Density increase gt Min-power is more
effective
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Original Network
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Minhop v.s. Minpower at Time 1000
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Minhop v.s. Minpower at Time 2000
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Minhop and Minpower w/o constraint Consume
Similar Energy
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More node died in Minhop gt Minhop Consume Less
Energy at later time
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Conclusion

• Develop min power routing algorithm with hop
  constraint
• Network lifetime prolongs in this algorithm
• Energy savings are greater in Densor networks
• Next improvement try to do simulation in
  GlomoSim