Mobility Limited Flip-Based Sensor Networks Deployment Reporter: Po-Chung Shih Computer Science and...
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Transcript of Mobility Limited Flip-Based Sensor Networks Deployment Reporter: Po-Chung Shih Computer Science and...
Mobility Limited Flip-BasedSensor Networks Deployment
Reporter: Po-Chung Shih
Computer Science and Information Engineering DepartmentFu-Jen Catholic University
112/04/19
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Outline Introduction Related work
Edmonds-Karp algorithm Assumption
SOLUTION Overview Mobility Model Constructing the Virtual Graph
Performance Conclusion
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Introduction It is not practical to manually position
sensors in desired locations.
In this paper, we study deployment of sensor networks using mobile sensors.
Our problem is to determine a movement plan for the sensors in order to maximize the sensor network coverage and minimize the number of flips.
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Introduction A certain number of flip-based sensors are
initially deployed in the sensor network that is clustered into multiple regions.
(a) movement plan (b) result
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(a) A snapshot of the sensor network and the optimal movement plan.
(b) The resulting deployment.
Introduction
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Outline Introduction Related work
Edmonds-Karp algorithm Assumption
SOLUTION Overview Mobility Model Constructing the Virtual Graph
Performance Conclusion
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Edmonds-Karp algorithm Use BFS to find the augmenting path. The augmenting path is a shortest path from s to t in
the residual network. Running Time of Edmonds-Karp algorithm : O(VE2). Given a network of seven nodes, source A, sink G,
and capacities as shown below:
Related work
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Assumption All the sensors are mobile.
Each sensor knows its position.
The sensor network is a square field. It is divided into two-dimensional regions, where each region is a square of size R.
{ } R, where and are sensing
and transmission ranges of the sensors. i.e., R =m*d
Sensors can flip only once to a new location.
Related work
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2trsen SS min senS trS
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Outline Introduction Related work
Edmonds-Karp algorithm Assumption
SOLUTION Overview Mobility Model Constructing the Virtual Graph
Performance Conclusion
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SOLUTION Overview
Phase 1 :Each sensor in the network will first determine its position and the region it resides in.
Phase 2 :Sensors then forward their location information to the base-station (region-head).
Phase 3 :The base-station using the region information to determine the movement plan.
Phase 4 :The base-station will then forward the movement plan to corresponding sensors in the network.
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SOLUTION Mobility Model
First : The distance to which a sensor can flip is fixed and is equal to F.
Second : Sensors can flip to distances between 0 and F.
Parameters definition F : The maximum distance a sensor can flip. d : F is an integral multiple of the basic unit d. ( sensors can flip once to distances d, 2d, 3d, . . . nd from its
current location, where nd = F ).
C : C=n denotes the sensor has n choices for the flip distance ( between d and maximum distance F ).
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Parameters definition (Cont.) Hole : Region without any
sensor. Source : Region with at least
two sensors. Forwarder : Region with only
one sensor.
EX1 :F=d , C=1 , reachable regions of region 1 are regions 2 and 5.
EX2 :F=2d , C=1 , reachable regions of region 1 are regions 3 and 9.
EX3 :F=2d , C=n , reachable regions of region 1 are regions 2,3,5, and 9.
SOLUTION
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SOLUTION Constructing the Virtual Graph for the Case
R = d , F = d , C = 1
Case2 R = d , F = 2d , C = 1
Case3 R = d , F = 2d , C = n
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SOLUTION Theorem 1. Let be the minimum-cost
maximum-flow plan in GV . Its corresponding flip
plan will maximize coverage and minimize
the number of flips.
VWopt
SWopt
VWoptSWopt
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Outline Introduction Related work
Edmonds-Karp algorithm Assumption
SOLUTION Overview Mobility Model Constructing the Virtual Graph
Performance Conclusion
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Performance• Qi : The number of regions with at least one sensor at initial
deployment.
• Qo : The number of regions with at least one sensor after the movement plan determined by our solution is executed.
• CI = Qo – Qi (Coverage Improvement)
• FD=J/Qo – Qi (Denoting J as the optimal number of flips as determined by our solution).
• Network sizes : 300*300 units and 150*150 units.
• The region sizes are R = 10 and R = 20 units.
• The basic unit of flip distance d = 10 units. C=1 and C=n.
• The number of sensors deployed is equal to the number of regions.
• PN = P/Q (Denoting P as the total number of packets (or messages) sent and Q as the number of regions).
• : Different distributions in initial deployment.
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Outline Introduction Related work
Edmonds-Karp algorithm Assumption
SOLUTION Overview Mobility Model Constructing the Virtual Graph
Performance Conclusion
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Conclusion We proposed a minimum-cost maximum-
flow based solution to optimize coverage and the number of flips.