Sensor Deployment Based on Virtual Forces
Reference:
Yi Zou and Krishnendu Chakarabarty, “Sensor Deployment and
Target Localization Based on Virtual Forces”, Department of Electrical
and Computer Engineering, Duke University, IEEE INFOCOM 2003
2007. 10. 4
Hong Jae-Young
KAIS
T
Contents
Introduction
Related Prior Work
Virtual Force Algorithm
Simulation Results
Conclusion
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Introduction
The effectiveness of distributed sensor networks (DSN)
Depends on the sensor deployment
Coverage, communication cost, resource management
Random deployment
Practical for military applications
Not always lead to effective coverage
New sensor placement strategy
Maximize the coverage for a given number of sensors
Virtual Force Algorithm (VFA) as a sensor deployment of sensors
Enhance the coverage after initial random placement of sensors
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Related Prior Work
A variety of work for Sensor deployment problems
A bidding Protocol for Deploying Mobile Sensor
Sensor Deployment and Sensor Planning for Elusive Targets
A priori knowledge about possible target
No information about potential target
Mobile Sensor Network Deployment Using Potential Field
Each robot is a sensor node
Expensive and a large amount of computation
Coverage problems in wireless ad-hoc sensor networks
Self-localization
Sensor nodes are should be highly mobile and move frequently
Radar and sonar coverage
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Virtual Force Algorithm : VFA (1/7)
Basic assumptions
After the initial random deployment, all sensor nodes are able to
communicate with the cluster head
The cluster head is responsible for executing the VFA and managing the
one-time movement of sensors to the desired locations
Basic idea of VFA
Each sensor behaves as a “Source of force” for all other sensors
Positive (Attractive) vs. Negative (Repulsive)
Globally uniform sensor placement
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Virtual Force Algorithm : VFA (2/7)
Sensor Detection Models
Consider an n by m sensor field grid
K sensor deployed in the random deployment stage
Each sensor has a detection range r
P (x , y)
n
r
Let si deployed at point (xi , yi), any point P at (x , y)
d(si ,P)  (x i  x)  (yi  y)
2
r
2
r
m
Binary Sensor Detection Model
Probabilistic Sensor Detection Model
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Virtual Force Algorithm : VFA (3/7)
Virtual Forces
Notation
Let the total force action on sensor si be denoted by

Fi
Let the force exerted on si by another sensor sj be denoted by

FiR
Let total attractive force on si by F
iA

Fij
Let total repulsive force on si by
Virtual force calculation in the VFA

Total force Fi
on si,

Fi 
 

 Fij  FiR  FiA
k
j 1, j i
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Virtual Force Algorithm : VFA (4/7)
An example of virtual forces with four sensors
 


F1  F12  F13  F14
If we assume that d12>dth , d13<dth , d14=dth ,
s2 exerts an attractive force on s1,
s3 exerts a repulsive force on s1,
s4 exerts no force on s1
If re=0 then Binary sensor detection model
Make dij as close to 2r as possible
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Virtual Force Algorithm : VFA (5/7)
Non-overlapped and overlapped sensor coverage areas
Non-overlapped area
Overlapped area
Non-overlapped area
Minimize “wasted overlap”
A few grid points are not covered by any sensor
Overlapped area
More sensors for grid coverage
Therefore, adopt the Non-overlapped area
Total Coverage area is kr 2
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Virtual Force Algorithm : VFA (6/7)
If re>0, re is not negligible
Probabilistic Sensor Detection Model
Grid points are not covered with the same probability
Necessary overlap sensor detection areas
cx , y (si , s j )  1  (1  cx, y (si ))(1  cx, y (s j ))
cx, y (sov )  1 
 (1  c
x, y
(si ))
si Sov
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Virtual Force Algorithm : VFA (7/7)
Coverage Evaluation
Virtual Forces among sensors
Move sensor virtually
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Simulation Results (1/5)
Parameters
A total of 20 sensors
Random placement
Detection radius as 5 unit (r=5)
Large detection error as 3 unit (re=3)
50 by 50 sensor field
Pentium III 1.0GHz PC using MATLAB
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Simulation Results (2/5)
Binary Sensor Detection Model
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Simulation Results (3/5)
Binary Sensor Detection Model
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Simulation Results (4/5)
Probabilistic sensor detection model
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Simulation Results (5/5)
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Conclusion
Virtual Force Algorithm
Practical approach for sensor deployment
Advantages
Negligible computation time
Small amount of computation
One time repositioning of the sensors
Low-cost
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Questions & Comments
Any Questions?
Comments?
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