Dynamic Clustering forAcoustic Target Tracking inWireless Sensor Network

Wei-Peng Chen, Jennifer C. Hou, Lui Sha

Presented by Ray LamOct 23, 2004

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Outline

Introduction to sensor network Technical background for the system The dynamic clustering algorithm Limitations of the system Conclusion

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Sensor Network

Nodes in the network Sensor to sense

physical environment On-board processing,

limited capability Wireless

communication Limited power from

batteries

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The Network

The network 2 kinds of nodes:

source and sink Wireless network

Berkeley motes use CSMA MAC

Ad-hoc type Multi-hop routing Nodes sleep

periodically

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Data Dissemination

Some research questions How to coordinate sensors? How to route data? How to do in-network data fusion? What to do with congestion? How to do the above efficiently…

in terms of energy? in terms of time?

We need distributed solutions

The Acoustic Target Tracking System

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Energy-based Localization

Signal strength decreases exponentially with propagation distance

iii xxar

: received signal strength in the ith sensor: strength of an acoustic signal from the target: target position yet to be determined: known position of the ith sensor: attenuation coefficient: white Gaussian noise

irRa2Rx2Rxi

i

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Energy-based Localization

With a pair of energy readings Target is closer to sensor i than to sensor j

ji rr

j

i

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Energy-based Localization

Voronoi diagram 2-D space divided into Vor

onoi cells V(pi): Voronoi cell containin

g node pi

V(pi) contains all points closer to pi than to any other pj

ri larger than all neighbors’ readings only if target in V(pi)

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Network Characteristics

Network structure: 2-layer hierarchyStatic backbone of sparse cluster headsDense sensors for detecting targets

Radio transmission range = 2 * signal detection rangeEnsure 1 cluster at a timeEnsure nodes in a cluster hear each other

directly

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The Dynamic Clustering Algorithm

4 component mechanisms Initial distance calibration and tabulationCluster head (CH) volunteeringSensor replyingReporting of tracking results

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Idea of the Algorithm

Objective: minimize messages sent in the network and avoid collisions

Given an energy reading, estimate distance from target

Using Voronoi diagram, estimate probability that target is in my Voronoi cell

In CH volunteering and sensor replying process Nodes with high probability speak quickly When you hear a higher energy reading from others,

you give up speaking

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Initial Distance Calibration and Tabulation Each sensor to know 2-D coordinates of al

l other sensors in its transmission range Each CH constructs a Voronoi diagram for

neighboring CHs Each sensor (including CH) constructs a V

oronoi diagram for neighboring sensors

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Initial Distance Calibration and Tabulation Each CHi pre-computes for different

d Target on the circle centered at CHi with radiu

s d : conditional probability that target locat

es within V(CHi) given d3 cases…

diPr

/1/ ard

diPr

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Three Cases

d < radius of inner circle:

d > radius of outer circle:

In between: Take sample points on the

circle Check location of each poi

nt Estimate as # of sam

ple points inside V(CHi) / total # of sample points

1Pr di

0Pr di

diPr

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Initial Distance Calibration and Tabulation Sensors do similarly Each sensor Sj pre-computes for

different ri: energy reading from CHi

rj: energy reading of Sj

: conditional probability that target locates in V(Sj) given

jirj Prjir

jiji rrr /

jirj Prjir

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CH Volunteering

Distributed election algorithm CH closest to target should be elected Solicitation packet

Request to form cluster and volunteer to be the cluster head

Contains signal signatureContains signal strength detected by CH (CHi)

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CH Volunteering

Random delay-based broadcast mechanism CHi detects a signal, estimates d, checks

Sets a back-off timer with back-off time

CHi does not broadcast solicitation packet until timer expires

If during back-off, hears other solicitation packets with higher energy readings, gives up volunteering

diPr

ranWUdiWWWD Pr1minmaxmin

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Sensor Replying

Sensor Sj receives a solicitation packet Matches signal signature with buffered dat

a Upon a match, calculates signal strength rj

Attempts to send a reply using similar delay-based mechanism

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Sensor Replying

Random delay-based broadcast mechanism Calculates , checks Sets back-off timer with back-off time

If during back-off, hears other reply packets, records the sensor that reports largest signal strength

When timer expires, sends reply packet if rj higher than all others’ energy readings; or Sj is a Voronoi neighbor of the sensor that reports the largest si

gnal strength

jir jirj Pr

ranji WUrjWWWD Pr1minmaxmin

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Reporting Tracking Results

CH receives replies from sensors Sufficient number of replies:

A reply from Sj with largest signal strength

Replies from all Sj’s Voronoi neighbors

Takes location of Sj as location of target Sends result to sink through static backbon

e

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Limitations

Limited application space Not applicable to general monitoring applications

without “target” Signals must attenuate with propagation distance

1 cluster for 1 signal Signals may come simultaneously Multiple clusters may form simultaneously causing

more collisions

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Limitations

Energy inefficiencyRadio transmission range = 2 * signal

detection rangeCan be improved by considering multi-hop

routingSignals at any position must be detected by at

lease 1 CH Tradeoff of sensor density and energy efficiency

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Conclusion

Data dissemination in sensor network Dynamic clustering triggered per signal More research on:

Collision behavior between clustersMulti-hop routingTime efficient data dissemination

Discussion

The End

Thank you for coming!