The Community for Technology Leaders
RSS Icon
Issue No.01 - January (2010 vol.9)
pp: 73-86
Xue Wang , Tsinghua University, Beijing
Junjie Ma , Tsinghua University, Beijing
Sheng Wang , Tsinghua University, Beijing
Daowei Bi , Tsinghua University, Beijing
Energy constraint is an important issue in wireless sensor networks. This paper proposes a distributed energy optimization method for target tracking applications. Sensor nodes are clustered by maximum entropy clustering. Then, the sensing field is divided for parallel sensor deployment optimization. For each cluster, the coverage and energy metrics are calculated by grid exclusion algorithm and Dijkstra's algorithm, respectively. Cluster heads perform parallel particle swarm optimization to maximize the coverage metric and minimize the energy metric. Particle filter is improved by combining the radial basis function network, which constructs the process model. Thus, the target position is predicted by the improved particle filter. Dynamic awakening and optimal sensing scheme are then discussed in dynamic energy management mechanism. A group of sensor nodes which are located in the vicinity of the target will be awakened up and have the opportunity to report their data. The selection of sensor node is optimized considering sensing accuracy and energy consumption. Experimental results verify that energy efficiency of wireless sensor network is enhanced by parallel particle swarm optimization, dynamic awakening approach, and sensor node selection.
Wireless sensor networks, power management, target tracking, collaborative sensing, optimization.
Xue Wang, Junjie Ma, Sheng Wang, Daowei Bi, "Distributed Energy Optimization for Target Tracking in Wireless Sensor Networks", IEEE Transactions on Mobile Computing, vol.9, no. 1, pp. 73-86, January 2010, doi:10.1109/TMC.2009.99
[1] A. Sinha and A. Chandrakasan, “Dynamic Power Management in Wireless Sensor Networks,” IEEE Design and Test of Computers, vol. 18, no. 2, pp. 62-74, Mar. 2001.
[2] J. Wu and S. Yang, “SMART: A Scan-Based Movement-Assisted Sensor Deployment Method in Wireless Sensor Networks,” Proc. IEEE INFOCOM, pp. 2313-2324, Mar. 2005.
[3] S. Zhou, M. Wu, and W. Shu, “Finding Optimal Deployments for Mobile Sensors: Wireless Sensor Network Topology Adjustment,” Mobile and Wireless Comm., pp. 529-532, Mar. 2004.
[4] X. Wang, S. Wang, and J. Ma, “Dynamic Deployment Optimization in Wireless Sensor Networks,” Lecture Notes in Control and Information Sciences, pp. 182-187, Springer, Mar. 2006.
[5] H. Gupta and Z. Zhou, “Connected Sensor Cover: Self-Organization of Sensor Networks for Efficient Query Execution,” IEEE/ACM Trans. Networking, vol. 14, no. 1, pp. 55-67, Feb. 2006.
[6] R. Madan and S. Lall, “Distributed Algorithms for Maximum Lifetime Routing in Wireless Sensor Networks,” IEEE Trans. Wireless Comm., vol. 5, no. 8, pp. 2185-2193, Aug. 2006.
[7] L. Zou, M. Lu, and Z. Xiong, “A Distributed Algorithm for the Dead End Problem of Location Based Routing in Sensor Networks,” IEEE Trans. Vehicular Technology, vol. 54, no. 4, pp. 1509-1522, July 2005.
[8] Y. Yu and Q. Cheng, “Particle Filters for Maneuvering Target Tracking Problem,” Signal Processing, vol. 80, pp. 195-203, Jan. 2006.
[9] F. Gustafsson and F. Gunnarsson, “Particle Filters for Positioning, Navigation and Tracking,” IEEE Trans. Signal Processing, vol. 50, no. 2, pp. 425-437, Feb. 2002.
[10] N.B. Karayiannis, “Maximum Entropy Clustering Algorithms and Their Application in Image Compression,” Proc. 1994 IEEE Int'l Conf. Systems, Man, and Cybernetics, “Humans, Information, and Technology,” vol. 1, pp. 337-342, 1994.
[11] J. Yao and M. Dash, “Entropy-Based Fuzzy Clustering and Modeling,” Fuzzy Sets and Systems, vol. 3, pp. 282-188, Feb. 2000.
[12] M. Noto and H. Sato, “A Method for the Shortest Path Search by Extended Dijkstra Algorithm,” Proc. IEEE Int'l Conf. Systems, Man, and Cybernetics, pp. 2316-2320, Mar. 2000.
[13] T.D. Sudhakar, “Supply Restoration in Distribution Networks Using Dijkstra's Algorithm,” Proc. IEEE Int'l Conf. Power System Technology, pp. 640-645, Nov. 2004.
[14] M. Cardei and M.T. Thai, “Energy-Efficient Target Coverage in Wireless Sensor Networks,” Proc. IEEE INFOCOM, pp. 1976-1984, Mar. 2005.
[15] R.M. Passos and C.J.N. Coelho, “Dynamic Power Management in Wireless Sensor Networks: An Application-Driven Approach,” Proc. Int'l Conf. Wireless On-Demand Network Systems and Services, pp. 109-118, Jan. 2005.
[16] B. Hohlt and L. Doherty, “Flexible Power Scheduling for Sensor Networks,” Proc. Int'l Symp. Information Processing in Sensor Networks, pp. 205-214, Apr. 2004.
[17] N. Ahmed et al. “Performance Evaluation of a Wireless Sensor Network Based Tracking System,” Proc. Fifth IEEE Int'l Conf. Mobile Ad Hoc and Sensor Systems, pp. 163-172, Sept./Oct. 2008.
[18] S. Meguerdichian and F. Koushanfar, “Coverage Problems in Wireless Ad-Hoc Sensor Networks,” Proc. IEEE INFOCOM, pp.1380-1387, Mar. 2001.
[19] S.S. Dhillon and K. Chakrabarty, “Sensor Placement for Effective Coverage and Surveillance in Distributed Sensor Networks,” Proc. IEEE Wireless Comm. and Networking, pp. 1609-1614, Mar. 2003.
[20] Y. Qu and Y. Zhai, “A Novel Sensor Placement Model in Wireless Sensor Network,” J. Beijing Univ. of Posts and Telecomm., vol. 27, pp. 1-5, Feb. 2004.
[21] X. Bai and S. Kumar, “Deploying Wireless Sensors to Achieve Both Coverage and Connectivity,” Proc. ACM MobiHoc, pp.131-142, May 2006.
[22] D.M. Blough and M. Leoncini, “The K-Neighbors Approach to Interference Bounded and Symmetric Topology Control in Ad Hoc Networks,” IEEE Trans. Mobile Computing, vol. 5, no. 9, pp.1267-1282, Sept. 2006.
[23] S. Slijepcevic and M. Potkonjak, “Power Efficient Organization of Wireless Sensor Networks,” Proc. IEEE Int'l Conf. Comm., pp. 472-476, June 2001.
[24] P.D. Hanlon and P.S. Maybeck, “Characterization of Kalman Filter Residuals in the Presence of Mismodeling,” IEEE Trans. Aerospace and Electronic Systems, vol. 36, no. 1, pp. 114-131, Jan. 2000.
[25] H.A.P. Blom and E.A. Bloem, “Exact Bayesian and Particle Filtering of Stochastic Hybrid Systems,” IEEE Trans. Aerospace and Electronic Systems, vol. 43, no. 1, pp. 55-70, Jan. 2007.
[26] O. Payne and A. Marrs, “An Unscented Particle Filter for GMTI Tracking,” Proc. IEEE Aerospace Conf., pp. 1869-1875, Mar. 2004.
[27] X. Wang, S. Wang, and J. Ma, “An Improved Particle Filter for Target Tracking in Sensor System,” Sensors, vol. 7, pp. 144-156, Jan. 2005.
[28] X. Wang, A. Jiang, and S. Wang, “Mobile Agent Based Wireless Sensor Network for Intelligent Maintenance,” Lecture Notes in Computer Science, pp. 316-325, Springer, Mar. 2005.
[29] X. Wang and S. Wang, “Collaborative Signal Processing for Target Tracking in Distributed Wireless Sensor Networks,” J. Parallel and Distributed Computing, vol. 67, pp. 501-515, Mar. 2007.
[30] W.P. Chen, J.C. Hou, and L. Sha, “Dynamic Clustering for Acoustic Target Tracking in Wireless Sensor Networks,” IEEE Trans. Mobile Computing, vol. 3, no. 3, pp. 258-271, July-Sept. 2004.
[31] K. Chakrabarty and S.S. Iyengar, “Grid Coverage for Surveillance and Target Location in Distributed Sensor Networks,” IEEE Trans. Computers, vol. 51, no. 12, pp. 1448-1453, Dec. 2002.
[32] S. Li and C. Xu, “Sensor Deployment Optimization for Detecting Maneuvering Targets,” Proc. Int'l Conf. Information Fusion, pp.1629-1635, Apr. 2005.
[33] L. Yang and C. Feng, “Adaptive Tracking in Distributed Wireless Sensor Networks,” Proc. IEEE Int'l Symp. and Workshop Eng. Computer Based Systems, pp. 103-111, Mar. 2006.
[34] F.B. Duh and C.T. Lin, “Tracking a Maneuvering Target Using Neural Fuzzy Network,” IEEE Trans. System, Man, and Cybernetics, vol. 34, no. 1, pp. 16-33, Feb. 2004.
[35] Y. Oshman and P. Davidson, “Optimization of Observer Trajectories for Bearings-Only Target Localization,” IEEE Trans. Aerospace and Electronic Systems, vol. 35, no. 3, pp. 892-902, July 1999.
[36] L.R. Paradowski, “Uncertainty Ellipses and Their Application to Interval Estimation of Emitter Position,” IEEE Trans. Aerospace and Electronic Systems, vol. 33, no. 1, pp. 126-133, Jan. 1997.
[37] A.S. Chhetri and D. Morrell, “Energy Efficient Target Tracking in a Sensor Network Using Non-Myopic Sensor Scheduling,” Proc. Int'l Conf. Information Fusion, pp. 558-565, Feb. 2005.
[38] L. Wang, H. Ji, and X. Gao, “Clustering Based on Possibilistic Entropy,” Proc. Seventh Int'l Conf. Signal Processing, pp. 1467-1470, Mar. 2004.
[39] J.L. Sobrinho, “Algebra and Algorithms for QoS Path Computation and Hop-by-Hop Routing in the Internet,” IEEE/ACM Trans. Networking, vol. 10, no. 4, pp. 541-550, Aug. 2002.
[40] J. Kennedy and R. Eberhart, “Particle Swarm Optimization,” Proc. IEEE Int'l Conf. Neural Networks, vol. 4, pp. 1942-1948, Nov./Dec. 1995.
[41] G. Ciuprina, D. Ioan, and I. Munteanu, “Use of Intelligent-Particle Swarm Optimization in Electromagnetics,” IEEE Trans. Magnetics, vol. 38, no. 2, pp. 1037-1040, Mar. 2002.
[42] X. Wang, S. Wang, and J. Ma, “An Improved Co-Evolutionary Particle Swarm Optimization for Wireless Sensor Networks with Dynamic Deployment,” Sensors, vol. 7, pp. 354-370, Mar. 2007.
[43] Y. Shi and R.C. Eberhart, “Fuzzy Adaptive Particle Swarm Optimization,” Proc. Congress Evolutionary Computation, pp.1945-1950, Aug. 1999.
[44] X. Wang, J. Ma, S. Wang, and D. Bi, “Prediction-Based Dynamic Energy Management in Wireless Sensor Networks,” Sensors, vol. 7, pp. 251-266, Mar. 2007.
23 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool