The Community for Technology Leaders
RSS Icon
Issue No.04 - April (2009 vol.8)
pp: 433-444
Abdelmorhit El Rhazi , Ecole Polytechnique de Montréal, Montréal
The main challenge in wireless sensor network deployment pertains to optimizing energy consumption when collecting data from sensor nodes. This paper proposes a new centralized clustering method for a data collection mechanism in wireless sensor networks, which is based on network energy maps and Quality-of-Service (QoS) requirements. The clustering problem is modeled as a hypergraph partitioning and its resolution is based on a tabu search heuristic. Our approach defines moves using largest size cliques in a feasibility cluster graph. Compared to other methods (CPLEX-based method, distributed method, simulated annealing-based method), the results show that our tabu search-based approach returns high-quality solutions in terms of cluster cost and execution time. As a result, this approach is suitable for handling network extensibility in a satisfactory manner.
Wireless sensor network, energy map, data collect, clustering methods, tabu search.
Abdelmorhit El Rhazi, "A Tabu Search Algorithm for Cluster Building in Wireless Sensor Networks", IEEE Transactions on Mobile Computing, vol.8, no. 4, pp. 433-444, April 2009, doi:10.1109/TMC.2008.125
[1] P.K. Agarwal and C.M. Procopiuc, “Exact and Approximation Algorithms for Clustering,” Algorithmica, vol. 33, no. 2, pp. 201-226, June 2002.
[2] P. Basu and J. Redi, “Effect of Overhearing Transmissions on Energy Efficiency in Dense Sensor Networks,” Proc. Third Int'l Symp. Information Processing in Sensor Networks (IPSN '04), pp. 196-204, Apr. 2004.
[3] A. El Rhazi and S. Pierre, “A Data Collection Algorithm Using Energy Maps in Sensor Networks,” Proc. Third IEEE Int'l Conf. Wireless and Mobile Computing, Networking, and Comm. (WiMob '07), 2007.
[4] S. Ghiasi, A. Srivastava, X. Yang, and M. Sarrafzadeh, “Optimal Energy Aware Clustering in Sensor Networks,” Sensors, pp.258-269, 2002.
[5] F. Glover, E. Taillard, and D. Werra, “A User's Guide to Tabu Search,” Annals of Operations Research, vol. 41, no. 14, pp. 3-28, May 1993.
[6] M. Gondran and M. Minoux, Graphes et Algorithmes, second ed. Editions Eyrolles, 1985.
[7] W. Heinzelman, A. Chandrakasan, and H. Balakrishnan, “An Application Specific Protocol Architecture for Wireless Microsensor Networks,” IEEE Trans. Wireless Comm., vol. 1, no. 4, pp.660-670, Oct. 2002.
[8] J.J. Lee, B. Krishnamachari, and C.C.J. Kuo, “Impact of Heterogeneous Deployment on Lifetime Sensing Coverage in Sensor Networks,” Proc. IEEE Sensor and Ad Hoc Comm. and Networks Conf. (SECON '04), pp. 367-376, 2004.
[9] W. Liang and Y. Liu, “Online Data Gathering for Maximizing Network Lifetime in Sensor Networks,” IEEE Trans. Mobile Computing, vol. 6, no. 1, pp. 2-11, Jan. 2007.
[10] S. Jeremy, The Boost Graph Library: User Guide and Reference Manual. Addison-Wesley, 2002.
[11] T. Kanugo, D.M. Mount, N.S. Netanyahu, C.D. Piatko, R. Silverman, and A.Y. Wu, “A Local Search Approximation Algorithm for $k$ -Means Clustering,” Proc. 18th Ann. ACM Symp. Computational Geometry (SoCG '02), pp. 10-18, 2002.
[12] S. Kirkpatrick, C.C. Gelatt Jr., and M.P. Vecchi, “Optimization by Simulated Annealing,” Science, vol. 220, pp. 671-680, 1983.
[13] S.R. Madden, M.J. Franklin, J.M. Hellerstein, and W. Hong, “TAG: Tiny Aggregation Service for Ad-Hoc Sensor Networks,” Proc. Fifth Symp. Operating Systems Design and Implementation (OSDI '02), pp. 131-146, 2002.
[14] O. Moussaoui, A. Ksentini, M. Naimi, and M. Gueroui, “A Novel Clustering Algorithm for Efficient Energy Saving in Wireless Sensor Networks,” Proc. Seventh Int'l Symp. Computer Networks (ISCN '06), pp. 66-72, 2006.
[15] S. Raghuwanshi and A. Mishra, “A Self-Adaptive Clustering Based Algorithm for Increased Energy-Efficiency and Scalability in Wireless Sensor Networks,” Proc. IEEE 58th Vehicular Technology Conf. (VTC '03), vol. 5, pp. 2921-2925, 2003.
[16] O. Younis and S. Fahmy, “Distributed Clustering in Ad-Hoc Sensor Networks: A Hybrid, Energy-Efficient Approach,” Proc. IEEE INFOCOM, pp. 629-640, 2004.
[17], Feb. 2007.
[18], Feb. 2008.
[19] http:/, Feb. 2008.
22 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool