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Issue No.07 - July (2011 vol.10)
pp: 1028-1041
Xue Wang , Tsinghua University, Beijing
Sheng Wang , Tsinghua University, Beijing
ABSTRACT
Sensor nodes deployment is very crucial for wireless sensor networks (WSNs). Current methods are apt to enlarge the coverage by achieving a nearly even deployment with similar density in the whole network. However, in some specific applications, the even distribution may not satisfy the sensing requirements. This paper proposes a virtual force directed coevolutionary particle swarm optimization (VFCPSO) algorithm, which uses a combined objective function to achieve the tradeoff of coverage and energy consumption. By considering deployment as an optimization problem, VFCPSO is more reliable and flexible for WSNs, since it can satisfy the combined requirements instead of only enlarging coverage. For investigating the performance of different paradigms, centralized VFCPSO is extended to distributed VFCPSO, heterogeneous hierarchical VFCPSO and homogeneous hierarchical VFCPSO (Homo-H-VFCPSO), and the solution of preferential deployment in interested region is also analyzed. Simulation results show that the Homo-H-VFCPSO has the best performance, i.e., it is more efficient than other three VFCPSO algorithms and the VF-style algorithms in terms of computation time, coverage and efficient moving energy consumption. It is obvious that the Homo-H-VFCPSO has good global searching ability and scalability, and it can rapidly and effectively achieve the sensor nodes deployment in WSNs.
INDEX TERMS
Wireless sensor networks, deployment, particle swarm optimization, distributed artificial intelligence.
CITATION
Xue Wang, Sheng Wang, "Hierarchical Deployment Optimization for Wireless Sensor Networks", IEEE Transactions on Mobile Computing, vol.10, no. 7, pp. 1028-1041, July 2011, doi:10.1109/TMC.2010.216
REFERENCES
[1] I.F. Akyildiz, W. Su, Y. Sankrasubramaniam, and E. Cayirci, "A Survey on Sensor Networks," IEEE Comm. Magazine, vol. 40, no. 8, pp. 102-114, Aug. 2002.
[2] K. Wu, Y. Gao, and F. Li, "Lightweight Deployment-Aware Scheduling for Wireless Sensor Networks," Mobile Networks and Applications, vol. 10, no. 6, pp. 837-852, Dec. 2005.
[3] S.S. Dhillon, K. Chakrabarty, and S.S. Iyengar, "Sensor Placement for Grid Coverage under Imprecise Detections," Proc. Fifth Int'l Conf. Information Fusion, pp. 1581-1587, 2002.
[4] G.T. Sibley, M.H. Rahimi, and G.S. Sukhatme, "Robomote: A Tiny Mobile Robot Platform for Large-Scale Sensor Networks," IEEE Int'l Conf. Robotics and Automation, pp. 1143-1148, 2002.
[5] T. Wong, T. Tsuchiya, and T. Kikuno, "A Self-Organizing Technique for Sensor Placement in Wireless Micro-Sensor Networks," Proc. 18th Int'l Conf. Advanced Information Networking and Applications, pp. 78-83, 2004.
[6] S. Li, C. Xu, W. Pan, and Y. Pan, "Sensor Deployment Optimization for Detecting Maneuvering Targets," Proc. Seventh Int'l Conf. Information Fusion, pp. 1629-1635, 2005.
[7] S. Yang, M. Li, and J. Wu, "Scan-Based Movement-Assisted Sensor Deployment Methods in Wireless Sensor Networks," IEEE Trans. Parallel and Distributed Systems, vol. 18, no. 8, pp. 1108-1121, Aug. 2007.
[8] S. Chellappan, X. Bai, B. Ma, D. Xuan, and C. Xu, "Mobility Limited Flip-Based Sensor Networks Deployment," IEEE Trans. Parallel and Distributed Systems, vol. 18, no. 2, pp. 199-211, Feb. 2007.
[9] B.S. Manoj, A. Sekhar, and C.S.R. Murthy, "On the Use of Limited Autonomous Mobility for Dynamic Coverage Maintenance in Sensor Networks," Computer Networks, vol. 51, no. 8, pp. 2126-2143, Aug. 2007.
[10] G. Wang, G. Cao, and T.F. La Porta, "Movement-Assisted Sensor Deployment," IEEE Trans. Mobile Computing, vol. 5, no. 6, pp. 640-652, June 2006.
[11] Y. Zou and K. Chakrabarty, "Sensor Deployment and Target Localization Based on Virtual Forces," Proc. IEEE INFOCOM, pp. 1293-1303, 2003.
[12] H. Shu, Q. Liang, and J. Gao, "Distributed Sensor Networks Deployment Using Fuzzy Logic Systems," Int'l J. Wireless Information Networks, vol. 14, no. 3, pp. 163-173, Sept. 2007.
[13] A. Howard, M.J. Matarić, and G.S. Sukhatme, "Mobile Sensor Network Deployment Using Potential Fields: A Distributed, Scalable Solution to the Area Coverage Problem," Proc. Sixth Int'l Symp. Distributed Autonomous Robotics Systems, June 2002.
[14] X. Wang, S. Wang, and J. Ma, "An Improved Co-Evolutionary Particle Swarm Optimization for Wireless Sensor Networks with Dynamic Deployment," Sensors, vol. 7, no. 3, pp. 354-370, Mar. 2007.
[15] M. Yang, Y. Cao, L. Tan, and J. Yu, "A New Self-Deployment Algorithm in Hybrid Sensor Network," Proc. Second Int'l Symp. Intelligent Information Technology Applications, pp. 268-272, Dec. 2008.
[16] J. Cortes, S. Martinez, T. Karatas, and F. Bullo, "Coverage Control for Mobile Sensing Networks," IEEE Trans. Robotics and Automation, vol. 20, no. 2, pp. 243-255, Apr. 2004.
[17] R. Eberhart and J. Kennedy, "A New Optimizer Using Particle Swarm Theory," Proc. Sixth Int'l Symp. Micro Machine and Human Science, pp. 39-43, 1995.
[18] Y. Shi and R.A. Krohling, "Co-Evolutionary Particle Swarm Optimization to Solve Min-Max Problems," Proc. Congress on Evolutionary Computation, pp. 1682-1687, 2002.
[19] F. Van DenBergh and A.P. Engelbrecht, "A Cooperative Approach to Particle Swarm Optimization," IEEE Trans. Evolutionary Computation, vol. 8, no. 3, pp. 225-239, June 2004.
[20] X. Wang, S. Wang, and J. Ma, Dynamic Deployment Optimization in Wireless Sensor Networks, vol. 344, pp. 182-187. Springer, 2006.
[21] X. Wang, J. Ma, and S. Wang, "Prediction-Based Dynamic Energy Management in Wireless Sensor Networks," Sensors, vol. 7, no. 3, pp. 251-266, Mar. 2007.
[22] N. Patwari and A. HeroIII, "Using Proximity and Quantized RSS for Sensor Location in Wireless Location in Wireless Networks," Proc. Workshop Wireless Sensor Networks and Applications, pp. 20-29, 2003.
[23] D. Niculescu and B. Nath, "Ad Hoc Positioning Systems Using AoA," Proc. IEEE INFOCOM, pp. 1734-1743, 2003.
[24] X. Wang and S. Wang, "Collaborative Signal Processing for Target Tracking in Distributed Wireless Sensor Networks," J. Parallel and Distributed Computing, vol. 67, no. 5, pp. 501-515, May 2007.
[25] N. Heo and P.K. Varshney, "Energy-Efficient Deployment of Intelligent Mobile Sensor Networks," IEEE Trans. Systems, Man and Cybernetics—Part A: Systems and Humans, vol. 35, no. 1, pp. 78-92, Jan. 2005.
[26] A. Howard, M.J. Mataric, and G.S. Sukhatme, "An Incremental Self-Deployment Algorithm for Mobile Sensor Networks," Autonomous Robots, vol. 13, no. 2, pp. 113-126, Sept. 2002.
[27] 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, Feb. 2002.
[28] F. Van Den Bergh and A.P. Engelbrecht, "A Study of Particle Swarm Optimization Particle Trajectories," Information Sciences, vol. 176, no. 8, pp. 937-971, Apr. 2006.
[29] J.M. Hereford, "A Distributed Particle Swarm Optimization Algorithm for Swarm Robotic Applications," Proc IEEE Congress on Evolutionary Computation, pp. 1678-1685, 2006.
[30] L. Wang, H. Ji, and X. Gao, "Clustering Based on Possibilistic Entropy," Proc. Seventh Int'l Conf. Signal Processing, pp. 1467-1470, 2004.
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