Mobility Improves Coverage of Sensor Networks

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Mobility Improves Coverage of Sensor Networks Benyuan Liu*, Peter Brass, Olivier Dousse, Philippe Nain, Don Towsley * Department of Computer Science University of Massachusetts - Lowell

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Mobility Improves Coverage of Sensor Networks. Benyuan Liu*, Peter Brass, Olivier Dousse, Philippe Nain, Don Towsley. * Department of Computer Science University of Massachusetts - Lowell. Outline. background and motivation mobility improves coverage summary and future work. - PowerPoint PPT Presentation

Transcript of Mobility Improves Coverage of Sensor Networks

Page 1: Mobility Improves Coverage of Sensor Networks

Mobility Improves Coverage of Sensor Networks

Benyuan Liu*, Peter Brass, Olivier Dousse, Philippe Nain, Don Towsley

* Department of Computer ScienceUniversity of Massachusetts - Lowell

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Outline

background and motivation

mobility improves coverage

summary and future work

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What is coverage ?

coverage: quality of surveillance of sensor networkhow well sensors cover a region of interest ? how effective sensor network detect intruders ?many different measures: area coverage, barrier

coverage, detection coverage, etc

important for surveillance sensor net applicationsbattlefield, infrastructure security

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Mobile sensor networks

coverage of stationary sensor network intensively studied

sensors can be mobile: mounted on robots or move with environments

Q: How does sensor mobility affect coverage?

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Previous work[Howard 02, Zou04, Wang 04]

sensors move to reach stationary configuration with better area coverage

several approaches proposed, different in how to compute desired locations for sensors (e.g., potential field, virtual force, etc)

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Our work different perspective: coverage resulting from

continuous movement of sensors

1. mobility increases covered area stationary sensors: covered area doesn’t change over time mobile sensors: uncovered area may be covered later, more area

covered over time

we are interested in area coveragearea covered at specific time instant tarea covered over time interval [0, t) fraction of time a location is covered

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Our work2. mobility improves intrusion detection

stationary sensors: intruder won’t be detected if not move or moves along uncovered path

mobile sensors: may be detected by moving sensors

we are interested in detection time time before an intruder is first detected measure how quickly sensors detect intruders consider stationary and mobile intruders

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Our work

3. how should sensors and intruder move? intruder moves to maximize its detection timesensors minimize the maximum detection time

we are interested in optimal mobility strategies for both sensors and intruders game theoretic approach

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Network model

initial configuration sensors are deployed uniformly at random

sensor density: sensing range: r

mobility model each sensor chooses a random direction [0, 2)

according to distribution speed vs [0, vs

max] according to

)(f

)(vVf

simple model to obtain insight

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Area coverage

area coverage at any given time instant unchanged

21 reaf

)][22(1)( tsVrEretif

t

uncovered region will be covered, more area will

be covered for a time interval [0,t)

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Tradeoff: covered area and covered time

location alternates between covered and uncovered

)2exp(~ srVnT

21 retf

appropriate for delay-tolerant applications

fraction of time a point is covered

uncovered time:

covered time λr)/λπr(eTcE 212][

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Detection time: stationary intruder

intruder can be detected by moving sensors

detection time: time before first being detected, X

divide sensors into different classes according to direction

time takes to be first hit (detected) by a class i sensor:

)2exp(~ srViiX

Vs

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Detection time: stationary intruder

)2exp( srVX iXX min

to guarantee expected detection time smaller than T0

)2exp()( tsrVtXP

02/1 rTsV

can tradeoff sensor density with speed

detection time: smallest hit times among all classes

result:

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Mobile intruder: detection time

20 )()(

22cos

2ˆ41)(

1ˆ,/

dftwcsvsV

uccuw

ccsvtvc

)2exp( sVrX

convert to reference system where intruder is stationary detection time:

),( ttv

speedsensor effective :sV

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Mobile intruder: optimal strategy

target maximizes its lifetime

)],),(([,

max tvtfXEtvt

sensors minimize the maximum detection time

)],),(([,

max)(

min tvtfXEtvtf

a minimax optimization problem

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Optimal strategy: special cases

sensors: move in same direction

intruder: moves in same direction with same speed as sensor

sensors: choose direction uniformly in [0, 2)

intruder: stay stationary intuition: if intruder moves,

will hit oncoming sensors sooner

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Optimal strategy: solution

sensors choose direction uniformly target stay stationary

intuition: if not uniform, intruder will move in direction of highest probability density, resulting in longer detection time

21)( f

0tV

?

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Summary and future work

define coverage resulting from sensor mobility

derive analytical results to provide insight

future work: more general mobility and detection model collaboration among sensors

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Thank you!