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Sensor Deployment and Target Localization in Distributed Sensor Networks

Sensor Deployment and Target Localization in Distributed Sensor Networks. Yi Zou and Krishnendu Chakrabarty ACM Transactions on Embedded Computing Systems 2003 Speaker : Chen-Chi Hsieh. Outline. Introduction Virtual force algorithm Target localization Simulation results Conclusions.

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Sensor Deployment and Target Localization in Distributed Sensor Networks

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  1. Sensor Deployment and Target Localization in Distributed Sensor Networks Yi Zou and Krishnendu Chakrabarty ACM Transactions on Embedded Computing Systems 2003 Speaker:Chen-Chi Hsieh

  2. Outline • Introduction • Virtual force algorithm • Target localization • Simulation results • Conclusions

  3. Introduction-Motivations • Motivations • Distributed sensor networks (DSNs) are important for strategic applications • Target detection, surveillance, and localization • The effectiveness of DSNs is determined to the coverage provided by the sensor deployment • The positioning of sensors affects coverage, communication cost, and resource management

  4. Introduction (cont.) -Motivations • A random placement of sensors in the target area is often desirable • Especially if no a prior knowledge of the terrain is available • However, random deployment does not always lead to effective coverage

  5. Introduction (cont.) - Objectives • Objectives • Maximize the coverage for a given number of sensors within a cluster in cluster-based DSNs • Propose an energy-conserving method for novel target localization

  6. Introduction (cont.) - Key ideas • Key ideas in this paper • Coverage • A random deployment can be improved using a force-directed algorithm • Virtual force algorithm (VFA) • Target localization • Is based on a two-step communication protocol between the cluster head and the sensors within the cluster

  7. Virtual force algorithm- Environment • Environment:for a cluster-based sensor network architecture • All sensor nodes are able to communicate with the cluster head • The cluster head is responsible for executing the VFA algo. and managing the one-time movement of sensors to the desired locations • Sensors only send a yes/no notification message to the cluster head when a target is detected

  8. S1 S2 S3 Virtual force algorithm (cont.)- The virtual force ideas • The virtual force ideas • Each sensor behaves as a “source of force” for all other sensors S1 dth S2 S3

  9. Y S2 S3 S4 S1 Positive force (attractive force) X Negative force (repulsive force) Virtual force algorithm (cont.)- The virtual force ideas • The virtual force ideas • Each sensor behaves as a “source of force” for all other sensors

  10. Virtual force algorithm (cont.)- The virtual force ideas • Virtual Force calculation in the VFA algo. • : the vector exerted on Si by another sensor Sj • Obstacles and areas of preferential coverage also have forces acting on Si • :the total (attractive) force on Si due to preferential coverage areas • :the total (repulsive) force on Si due to obstacles • The total force on Si

  11. Virtual force algorithm (cont.)- The virtual force ideas • Express between Si and Sj in polar coordinate notation • dth:the threshold distance • αij:the angle of a line segment from Si to Sj • wA (wR) :the attractive (repulsive) force

  12. Virtual force algorithm (cont.)- Assumptions • Assumptions • An n by m sensor field grid • There are k sensors deployed in the random deployment stage • r:detection range of a sensor • Sensor Si is deployed at point (xi, yi) • d(Si, P) is the distance between Si and P, for any point P at (x, y)

  13. d(Si, P) < r P P r d(Si, P) ≧r Virtual force algorithm (cont.)- Coverage • The coverage cxy(Si) of a grid point P(x,y) by sensor Si • The binary sensor detection model Si

  14. re re Si r 1 e-λaβ 0 Si P Si Virtual force algorithm (cont.)- Coverage • The probabilistic sensor detection model • In reality, sensor detections are imprecise • re is the uncertainty in sensor detection • a = d (Si,P)-d (r-re) • λand β are parameters that measure detection probability

  15. Virtual force algorithm (cont.)- Coverage • cxy(Si,Sj):the probability that a target is detected by two sensors (overlapped) • A region which is overlapped by kov sensors Si Sj P

  16. Virtual force algorithm (cont.)- Energy Constraint on the VFA Algorithm • dmax:the max. distance that each node can move in repositioning phase

  17. Virtual force algorithm (cont.)- Procedural description of the VFA algorithm

  18. Virtual force algorithm (cont.)- Procedural description of the VFA algorithm

  19. Target localization- Detection Probability Table • The cluster head generates a detection probability table for each grid point • Contains all possible detection reports from sensors that can detect a target at this grid point P • Sxy:a grid point P(x,y) is covered by a set of kxy sensors • pxy(Sj, i) : • If Sj detects a target: pxy(Sj, i) =cxy(Sj) • otherwise: pxy(Sj, i) =1-cxy(Sj)

  20. Target localization- Detection Probability Table

  21. Target localization- Detection Probability Table

  22. Simulation Results • Environment • 50×50 sensor field • A total of 20 sensors in the sensor field in random placement stage • Each sensor • a detection radius:r=5 • Range detection error:re=3 • The simulation is done on a Pentium III 1.0GHz PC using Matlab

  23. Simulation Results-binary sensor detection model

  24. Simulation Results-binary sensor detection model

  25. Simulation Results-probability sensor detection model

  26. Simulation Results-probability sensor detection model

  27. Simulation Results-with obstacles and preferred areas

  28. Simulation Results-with obstacles and preferred areas

  29. Conclusion • The virtual force algorithm (VFA) • Uses a force-directed approach to improve the coverage after initial random deployment • Advantages • Negligible computation time • One-time repositioning of sensors • Flexibility

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