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Trade-offs Between Mobility and Density for Coverage in Wireless Sensor Networks Wei Wang, Vikram Srinivasan and Kee-Chaing Chua National University of Singapore 2007 Mobicom
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Outline Introduction Coverage with mobile sensors Coverage of hybrid networks Mobility algorithm Numerical results Conclusion
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Introduction Coverage problem Important research problem in WSNs k-covered Network Deployment Mobility
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Introduction- deployment Metric: over-provisioning factor Indicates the efficiency of a network deployment strategy Consider a random deployment strategy What is the sensor density to guarantee k-coverage?
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Introduction- mobility Mobile sensors can relocate themselves to heal coverage holes Over-provisioning factor for a network with all mobile sensors can be Θ(1) Consumes more energy Mobile sensors Limited mobility: move once, over a short distance Maximum distance?
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Coverage with mobile sensors Sensing field: L=l*l Num. of static sensors: N = λL Uniformly and independently scattered in the network. Number of static sensors in a region with area of A: n A Sensing range: r = 1 /√π 1=πr 2 1 Density
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Over-Provisioning Factor Optimal over-provisioning factor:Θ(1) d s = √2r Density of mobile sensor K-coverage r = 1 /√π
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Over-Provisioning Factor Randomly deployed static sensor networks Density λ Total expected area which is uncovered is e −λ L. Random coverage processes Large enough λ, e −λ can be made arbitrarily small Probability approaches one for a network with constant sensor density λ when the network size L→∞. Exist a connected coverage hole larger than unit area
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Over-Provisioning Factor To achieve k-coverage in a large network, the static sensor density needs to grow with the network size λ = logL +(k + 2) log log L + c(L) c(L) → +∞ as L → +∞
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All Mobile Networks η m = Θ(1). key question what is the maximum distance that each sensor has to move? Limit the maximum moving distance for each mobile
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All Mobile Networks maximum distance Theorem1: Network can provide k-coverage with an over-provisioning factor of η m = π/ 2 and the maximum distance moved by any mobile sensor is O( 1 √klog 3/4 (kL)) w.h.p.
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All Mobile Networks Sensing field into square grids with side length of d a =√2r/√k Number of nodes in the sensing range πr 2 /(√2r/√k) 2 =πk/2 η m =(πk/2) / k = π/2
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All Mobile Networks By the lower bounds on lattice points covered by a circle, there are at least W(k) lattice points of side length of d a covered by a circle of radius r d a =√2r/√k Increasing function
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All Mobile Networks W(k) > k when k ≥ 25 ->k coverage W(k)=25.13274 Network is at least k-covered when 1 ≤ k < 25.
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All Mobile Networks l × l square, L = l 2 points in the region there exists a perfect match between the L random points and the L grid points with maximum distance between any matched pairs of O(log3/4 L). Grid points (k/2r 2 )*L O(log 3/4 (kL)) Grid size is d a =√2r /√k O( 1/√k log 3/4 (kL)) 1=πr 2 1/r 2 = π η m =Densty/k Densty= η m *k= πk/2 =k/2r 2
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Coverage of hybrid networks Over-provisioning factor is O(1) Fraction of mobile sensors required is less than 1 /√2πk Maximum distance that any mobile sensor will have to move is O(log 3/4 L)
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Density of Mobile Sensors Static sensor density at λ =2πk. Divide the network into square cells equal side length of d h = r/√2. Average number of static sensors in each cell will be 2πkd 2 h = k.
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Density of Mobile Sensors The network will be k-covered if all cells contain at least k sensors. cell i has v i = k−n i vacancies, If a cell i contains n i < k static sensors Poisson approximation
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Density of Mobile Sensors The random variable v i = [k − n i ] +, will be distributed as: The expected number of vacancies in a cell will be:
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Density of Mobile Sensors Using Stirling’s approximation Density of mobile sensor Density of Static sensor Fraction of mobile sensors required is less than r = 1 /√π d h = r/√2.
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Maximum distance for mobiles A grid with side length of 1/ √Λ Maximum distance Decreasing function Matching distance
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Mobility Algorithm Problem Formulation Movement cost Initial number of mobile sensor Number of mobile sensor from cell i to cell j
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Distribution Solution A distributed algorithm Maximum flow problem Assume Sensor knows Its location Which cell it is located in. v i and m i Each cell elects a mobile or static sensor as the delegate Communicate and exchange information with its neighbors in graph G
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Distribution Solution- push-relabel algorithm a bc io oioi Cell a Cell c Distance D v-m=3 v-m=-2 v-m=-1
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Distribution Solution- push-relabel algorithm a bc io oioi Cell a Cell c h(i)=0 e(i)=0 h(i) =0 e(i) =0 h(i) =0 e(i) =0 h(o)=0 e(o)=3 h(o) =0 e(o) =-2 h(o)=0 e(o) =-1 Zero cost cici v-m=3 v-m=-2v-m=-1
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Distribution Solution- push-relabel algorithm a bc io oioi Cell a Cell c h(i)=0 e(i)=0 h(i) =0 e(i) =0 h(i) =0 e(i) =0 h(o)=0 e(o)=3 h(o) =0 e(o) =-2 h(o)=0 e(o) =-1 v-m=3 v-m=-2v-m=-1 h(o)=1 e(o)=3
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Distribution Solution- push-relabel algorithm a bc io oioi Cell a Cell c h(i)=0 e(i)=0 h(i) =0 e(i) =0 h(i) =0 e(i) =1 h(o) =0 e(o) =-2 h(o)=0 e(o) =-1 v-m=3 v-m=-2v-m=-1 h(o)=1 e(o)=2 h(o)=1 e(o)=1 h(i) =0 e(i) =1
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Distribution Solution- push-relabel algorithm a bc io oioi Cell a Cell c h(i)=0 e(i)=0 h(i) =0 e(i) =0 h(o) =0 e(o) =-1 h(o)=0 e(o) =1 v-m=3 v-m=-2v-m=-1 h(o)=1 e(o)=1 h(i) =0 e(i) =0
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Distribution Solution- push-relabel algorithm a bc io oioi Cell a Cell c h(i)=0 e(i)=0 h(i) =0 e(i) =0 h(o) =0 e(o) =-1 h(o)=0 e(o) =1 v-m=3 v-m=-2v-m=-1 h(o)=1 e(o)=1 h(i) =0 e(i) =1
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Numerical results Mobile Sensor Networks only consider the maximum matching distance for 1-coverage in our simulations M = ΛL mobiles Λ=π/2 d s= √2 r 10 5 randomly generated topologies Probability that no feasible matching exists for a given maximum moving distance D.
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dsds
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Numerical results Hybrid Networks Cells with side length of d h = r/√2 N = λL static sensors, λ = 2πk M = ΛL mobiles M is selected so that there are exactly enough mobiles to fill all vacancies Moving distance D
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k=10 d h =0.5 d s
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Cells=900
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Performance of Push-Relabel Algorithm Execution process is divided into rounds 10 3 randomly generated topologies Total number of messages Rounds
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Conclusion Investigate the distance that a mobile sensor will have to move Mobile sensor networks Hybrid sensor networks Results prove that Mobility has significant advantages in providing coverage
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