Achieving Long-Term Surveillance in VigilNet

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Achieving Long- Term Surveillance in VigilNet Pascal A. Vicaire Department of Computer Science University of Virginia Charlottesville, USA

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Achieving Long-Term Surveillance in VigilNet. Pascal A. Vicaire Department of Computer Science University of Virginia Charlottesville, USA. Motivating Application: Battlefield Surveillance. To Satellite. Other Applications. Wildlife Monitoring. Flock Protection. Alarm System. - PowerPoint PPT Presentation

Transcript of Achieving Long-Term Surveillance in VigilNet

Page 1: Achieving Long-Term Surveillance in VigilNet

Achieving Long-Term Surveillance

in VigilNetPascal A. Vicaire

Department of Computer Science

University of Virginia

Charlottesville, USA

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Motivating Application: Battlefield SurveillanceTo

Satellite

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Other Applications

Wildlife Monitoring

Alarm System

Flock Protection

Border Surveillance

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Power Consumption: An Important Issue in Surveillance Systems No power management 4 days lifetime!

Power management 10 months lifetime!

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State of the Art: Hardware

Power efficient hardware MICA2, MICAz, XSM, etc…

Energy scavenging hardware Vibrations. Roundy et al., “A Study of Low Level

Vibrations as a Power Source for Wireless Sensor Network”, Computer Communications, 2003.

Sun light. Perpetually powered Telos.

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State of the Art: Software

Synchronization and coordination: Nodes turn on only for specific tasks of which the execution time is known in advance.

Data aggregation and compression: Nodes reduce amount of transferred data to decrease energy costs.

Coverage control: Nodes providing redundant sensing coverage are turned off.

Duty cycle scheduling: Nodes alternate between on and off states at a fast rate, which still allow them to detect slow paced targets.

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Power Management in VigilNet Combination of three schemes in real system.

Duty CycleScheduling

TripwireService

SentryService

Node Level

Group Level

Network Level

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Putting Nodes Into a Sleep State

Toggle Period

Sleep 1% Wakeup Sleep

Preamble length = TogglePeriod * BitRate SYNC Bytes DATA CRC

Putting nodes to sleep as often and as long as possible. Sleeping mode: node wakeup 1% of the time.

Wakeup operation: send message with long preamble.

(1s)

(10ms)

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Group Level: Sentry Selection Redundant sensing coverage!

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Group Level: Sentry Selection Sentry selection and rotation.

Asleep

Awake

Sentry

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Group Level: Sentry Selection How are the sentries selected?

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Group Level: Sentry Selection 1. Neighbors exchange “hello” message

(ID + position + nb of neighbors + energy).

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Group Level: Sentry Selection 2. Each node selects a delay according to its

energy resources and coverage.

Delay = Function (Energy + Coverage)

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Group Level: Sentry Selection 3. Once the delay is elapsed, a node

announces itself as a sentry.

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Group Level: Sentry Selection Tradeoff: detection probability versus density.

TargetDetectionProbability

Number of Sentries inArea

10010 1,000

Sensing Radius=20mSensing Radius=8mSensing Radius=2m

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Node Level: Duty Cycle Scheduling Target takes time to go through the network.

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Node Level: Duty Cycle Scheduling Target takes time to go through the network

duty cycle scheduling.

Toggle Period (1s)

Asleep(800ms)

Awake (200ms)

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Node Level: Duty Cycle Scheduling Putting it all together.

Asleep

Awake

Sentry

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Node Level: Duty Cycle Scheduling Tradeoff: detection probability versus duty cycle.

Target DetectionProbability

Proportion of the TimeSentries are Awake

40%

100%

0% 20%

1000 Nodes, V=10m/s1000 Nodes, V=30m/s

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Network Level: Tripwire Scheduling Exploiting knowledge about the target.

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Network Level: Tripwire Scheduling Putting it all together.

Asleep

Awake

Sentry

Tripwire

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Network Level: Tripwire Scheduling Each base station defines a tripwire; a node pertains

to the tripwire associated with the closest base.

Tripwire

Node

Base Station

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Network Level: Tripwire Scheduling There are as many tripwires as base stations.

Tripwire

Node

Base Station

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Network Level: Tripwire Scheduling Tripwire schedule specification:

Tripwire1

Tripwire2

Tripwire3

Tripwire4

Tripwire5

Tripwire6

1

0

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Network Level: Tripwire Scheduling Tripwire schedule specification:

Tripwire1

Tripwire2

Tripwire3

Tripwire4

Tripwire5

Tripwire6

1

0

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1

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1

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Network Level: Tripwire Scheduling Tripwire schedule specification:

Tripwire1

Tripwire2

Tripwire3

Tripwire4

Tripwire5

Tripwire6

1

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Network Level: Tripwire Scheduling Tripwire schedule specification:

Tripwire1

Tripwire2

Tripwire3

Tripwire4

Tripwire5

Tripwire6

1

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Network Level: Tripwire Scheduling Tripwire schedule specification:

Tripwire1

Tripwire2

Tripwire3

Tripwire4

Tripwire5

Tripwire6

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Network Level: Tripwire Scheduling Tripwire schedule specification:

Tripwire1

Tripwire2

Tripwire3

Tripwire4

Tripwire5

Tripwire6

1

0

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Network Level: Tripwire Scheduling Tripwire schedule specification:

Tripwire1

Tripwire2

Tripwire3

Tripwire4

Tripwire5

Tripwire6

1

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Network Level: Tripwire Scheduling Tripwire schedule specification:

Tripwire1

Tripwire2

Tripwire3

Tripwire4

Tripwire5

Tripwire6

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On-Demand Wakeup

Wakeup PathTo Base StationFor Prompt Reporting

Detection Wakeup SurroundingNodes for Better Target Tracking, Target Classification,& Velocity Estimation

Asleep

Awake

Base Station

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Evaluation Methodology

Field

XSMsTripwire 1 Tripwire 2

Tripwire 3

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Evaluation Methodology

0

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Time (seconds)

En

erg

y(m

w)

Sentry

NonSentry

Initialization Duration = 5 minutes

Surveillance Duration = 1day

Without system rotation:NonSentry Life Time: 250 daysSentry LifeTime: 7 daysEne

rgy

(mW

s)

Time (s)

Initialization

Surveillance

SentryNon-Sentry

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Evaluation Results: Lifetime

0

50

100

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350

No PM + Sentry + Duty Cycle + Tripwire

Lifetime (days)

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Evaluation Results: Target Detection and Classification Average detection delay: 2.42 seconds. Average classification delay: 3.56 seconds. Classification of humans, humans with

weapons, and vehicles. Average delay to get velocity estimation:

3.75 seconds (average error: 6%).

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Summary

Successfully integrate 3 power management strategies into real surveillance system having a 10 months lifetime (source code available online).

Analytical model to predict system performance under various system configurations.

Simulation results exposing tradeoffs between detection performance and lifetime of the network.

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My Webpage: www.cs.virginia.edu/~pv9f

Tian’s Webpage:www.cs.umn.edu/~tianhe

Research Group Webpage:www.cs.virginia.edu/~stankovic/sensornet.html

Questions?