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Coverage and Energy Tradeoff in Density Control on Sensor Networks Yi Shang and Hongchi Shi University of Missouri-Columb ia ICPADS’05

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Page 1: Coverage and Energy Tradeoff in Density Control on Sensor Networks Yi Shang and Hongchi Shi University of Missouri-Columbia ICPADS’05

Coverage and Energy Tradeoff in Density Control

on Sensor NetworksYi Shang and Hongchi Shi

University of Missouri-Columbia

ICPADS’05

Page 2: Coverage and Energy Tradeoff in Density Control on Sensor Networks Yi Shang and Hongchi Shi University of Missouri-Columbia ICPADS’05

OutlineOutline

Introduction

Density Control ProtocolsNODC vs. OGDCDODCDNODCA

Experimental ResultsConclusions

Page 3: Coverage and Energy Tradeoff in Density Control on Sensor Networks Yi Shang and Hongchi Shi University of Missouri-Columbia ICPADS’05

IntroductionIntroduction Density Control

a technique for prolonging network’s lifetime while providing sufficient sensing coverage

determine when and which sensors should be powered up and which should power saving

Different applications require different degrees of sensing coverage complete coverage high percentage coverage

This paper consider the tradeoff between energy usage and coverage

Page 4: Coverage and Energy Tradeoff in Density Control on Sensor Networks Yi Shang and Hongchi Shi University of Missouri-Columbia ICPADS’05

Density Control ProtocolsDensity Control Protocols

NODC vs. OGDC ( Non-Overlapping vs. Optimal Geographical)

GODCOverlap= (20.9%)

NODCGap= (9.31%)

Page 5: Coverage and Energy Tradeoff in Density Control on Sensor Networks Yi Shang and Hongchi Shi University of Missouri-Columbia ICPADS’05

Density Control ProtocolsDensity Control Protocols

Assumptionsinterested sensing space is much larger than

the sensing range of each sensor noderadio range is at least twice of the sensing

rangeEach node knows its position

Page 6: Coverage and Energy Tradeoff in Density Control on Sensor Networks Yi Shang and Hongchi Shi University of Missouri-Columbia ICPADS’05

Density Control ProtocolsDensity Control Protocols

States: ON/OFF/UndecidedSelection of starting node

selecting starting node with probability p if its power exceeds a pre-determined threshold Pt

sets a backoff timer of τ1 secondsbroadcast a power-on message after backoff

position of the senderdirection α : uniform distribution in [0, 2π]

Page 7: Coverage and Energy Tradeoff in Density Control on Sensor Networks Yi Shang and Hongchi Shi University of Missouri-Columbia ICPADS’05

Density Control ProtocolsDensity Control Protocols

States: ON/OFF/UndecidedSelection of starting node

selecting starting node with probability p if its power exceeds a pre-determined threshold Pt

sets a backoff timer of τ1 secondsbroadcast a power-on message after backoff

position of the senderdirection α : uniform distribution in [0, 2π]

Page 8: Coverage and Energy Tradeoff in Density Control on Sensor Networks Yi Shang and Hongchi Shi University of Missouri-Columbia ICPADS’05

Density Control ProtocolsDensity Control Protocols

Actions: when receiving a power-on message checks the ratio of its sensing area covered by its

“ON” neighbors to its overall sensing area is over a predetermined threshold (turn-off threshold θ )

Rule R1: first power-on message received from starting node

Rule R2: first power-on message received from non-starting node

Rule R3: second power-on message received Rule R4: receive more than two power-on messages

Page 9: Coverage and Energy Tradeoff in Density Control on Sensor Networks Yi Shang and Hongchi Shi University of Missouri-Columbia ICPADS’05

Rule1

Rule3

Page 10: Coverage and Energy Tradeoff in Density Control on Sensor Networks Yi Shang and Hongchi Shi University of Missouri-Columbia ICPADS’05

Density Control ProtocolsDensity Control Protocols

Rule4: receive more than two power-on messages

1. None of the coverage areas of the senders overlaps

2. previous senders do not overlap andnew sender overlaps with previous senders

3. previous senders do not overlap and new sender overlaps with previous senders

AB

C

A B

CD D

Page 11: Coverage and Energy Tradeoff in Density Control on Sensor Networks Yi Shang and Hongchi Shi University of Missouri-Columbia ICPADS’05
Page 12: Coverage and Energy Tradeoff in Density Control on Sensor Networks Yi Shang and Hongchi Shi University of Missouri-Columbia ICPADS’05

ONDCDONDCDDensity Control Protocol Based on DistancesDensity Control Protocol Based on Distances

NODCD does not require the location informationRule R1: The message is the first power-on

message received.

Rule R2: More than one power-on messages have been received.

Page 13: Coverage and Energy Tradeoff in Density Control on Sensor Networks Yi Shang and Hongchi Shi University of Missouri-Columbia ICPADS’05

ONDCAONDCADensity Control with Adjustable Sensing RangesDensity Control with Adjustable Sensing Ranges

Turn-off threshold θ, 0 ≤ θ ≤ 1,Two iterations as follows

The optimal values of θ, r2 ????

Page 14: Coverage and Energy Tradeoff in Density Control on Sensor Networks Yi Shang and Hongchi Shi University of Missouri-Columbia ICPADS’05

Experimental ResultsExperimental Results

region of interest : 50m x 50m square.sensing range: rs = 5m.

constant c = 10/rs2

Page 15: Coverage and Energy Tradeoff in Density Control on Sensor Networks Yi Shang and Hongchi Shi University of Missouri-Columbia ICPADS’05

Experimental ResultsExperimental Results

88% vs. 85% 41 vs. 34 75 vs. 75

Page 16: Coverage and Energy Tradeoff in Density Control on Sensor Networks Yi Shang and Hongchi Shi University of Missouri-Columbia ICPADS’05

Experimental ResultsExperimental Results

Page 17: Coverage and Energy Tradeoff in Density Control on Sensor Networks Yi Shang and Hongchi Shi University of Missouri-Columbia ICPADS’05

Experimental ResultsExperimental Results

Page 18: Coverage and Energy Tradeoff in Density Control on Sensor Networks Yi Shang and Hongchi Shi University of Missouri-Columbia ICPADS’05

ConclusionsConclusions

three new density control protocols that apply new strategies in trading the coverage vs. energy usagedistributedeasy to implementlow computation/communication costs