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Deploying Sensors for Maximum Coverage in Sensor Network
Ruay-Shiung ChangShuo-Hung WangNational Dong Hwa University IEEE International Wireless Communications & Mobile Computing Conference 2007 (IWCMC 2007)
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Outline Introduction Self-Deployment by Density Control
(SDDC) Simulation Conclusion
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Introduction In the Wireless Mobile Sensor Network
The application of survivors searching efficiently search quick deployment large search area
The deployment should be considered about the sensing coverage the network communication
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Introduction
?
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Introduction
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Introduction
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Introduction There is the problem of deciding the
moving position The network partition The overlapping sensing coverage
Goal To deploy the sensor nodes with
larger sensing coverage unconnected networks
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Assumption Each Sensor
can get the data of obstacles positions measures the free area knows the neighbors’ distance and angle by [8]
the communication range > the sensing range Cx=2Sx
has one unique ID
[8]Relaxation on a mesh: a formalism for generalizedlocalization", Proceedings of the IEEE/RSJ InternationalConference on Intelligent Robots and Systems (IROS01),pages 1055--1060, Wailea, Hawaii, Oct 2001
obstacle
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Self-Deployment by Density Control
At the initialization The node exchange the ID with the
neighbors To decide the cluster-header
1
3
2
obstacle
Node id 1 2 3
Cluster statusNode status
Any pair of cluster headers are not in the communication range
Undecided Undecided Undecided
Not deployed
Not deployed
Not deployed
Clusterheader member member
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The cluster header Divides the communication into k
equal area calculates the density in
communication range The virtual force
the neighbor nodes The obstacles
Self-Deployment by Density Control
1
3
2
obstacle
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Density K: the parameter of division the
communication area Km : the measure of division of node’s
communication area
m
aa K
NDen
m
tt K
NDen 1
3
2
obstacle
area2area3
area4
area5
area6 area7
area8
area1
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The theoretical number is calculated by the related work.
Density
22227rKN m
t
The Geometrical Foundation of Natural Structure: A Source Book of Design R. Williams Dover Pub. Inc., New York, 1979.
krR
rKN m
t
1**227
227
2
2
22
If R=2r , k=8 Nt=0.41
There are 3 neighbors in the communication
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Density Ratio of actual number and theoretical number
The ratio of occupied area measure is defined
m
mmo K
OKR
The free area
t
a
mt
mam N
NKNKNR
//
The obstacle area ratio mm OK obstacle area
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Virtual Force Each node calculates the force within
it’s communication area
i
mi Dis
RF
1
3
2
obstacle
area2area3
area4
area5
area6 area7
area8
area1
o
oo Dis
RF
The Distance between the node i to nodes j
The Distance between the node to obstacle
Fi
Fo
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Self-Deployment by Density Control
In the cluster each node calculate the virtual force
oicom FFF
2
1
2
1
)()(
m
kyk
m
kxkcom FFF
2
1
2
11
)(
)(tan
m
kyk
m
kxk
F
F
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Self-Deployment by Density Control
The node get the new position and angle from the virtual force The node
Node status : not deployment Send the sug_msg to the neighbors
New position and angle Wait a ask_msg from other neighbor If there is no ask_msg feedback, node still waits a random time interval.
com
com
FRDis
DisRF
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Self-Deployment by Density Control
Sensors change the node status “not deployment“ to “deployed” adjust their position until the density lower than the Nt can not moving because the obstacle or other sensors Moving distance is small than the threshold β
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Self-Deployment by Density Control
The cluster header will communicate with the neighbor cluster header To compare with the cluster density ratio
Density ratio > neighbor’s ratioAll cluster move to the neighbor cluster
Density ratio <threshold εThe cluster stop moving
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Simulation Simulator : Stage multi-agent simulator Sensor nodes: 10-100 System parameter
Density ratio threshold : 0.125 Distance threshold: 1.25m
The moving speed : 0.6m/s The detection distance of obstacle : 5m
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Simulation
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Simulation Results
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Conclusion This paper proposes the Self-Deployment by
Density Control (SDDC) algorithm which deploys the sensor node quickly.
The simulation result shows that the algorithm is useful in spread the sensor nodes efficiently.