An Optimization Algorithm for the Maximum Lifetime Coverage Problems in Wireless Sensor Network

  • Ahn, Nam-Su (Daejeon Center, Defense Agency for Technology and Quality) ;
  • Park, Sung-Soo (Department of Industrial and Systems Engineering, KAIST)
  • Received : 2011.03.11
  • Accepted : 2011.09.14
  • Published : 2011.11.30

Abstract

In wireless sensor network, since each sensor is equipped with a limited power, efficient use of the energy is important. One possible network management scheme is to cluster the sensors into several sets, so that the sensors in each of the sets can completely perform the monitoring task. Then the sensors in one set become active to perform the monitoring task and the rest of the sensors switch to a sleep state to save energy. Therefore, we rotate the roles of the active set among the sensors to maximize the network lifetime. In this paper, we suggest an optimal algorithm for the maximum lifetime coverage problem which maximizes the network lifetime. For comparison, we implemented both the heuristic proposed earlier and our algorithm, and executed computational experiments. Our algorithm outperformed the heuristic concerning the obtained network lifetimes, and it found the solutions in a reasonable amount of time.

Keywords

References

  1. Agarwal, Y., K. Mathur, and H. M. Salkin, "A set-partitioning-based exact algorithm for the vehicle routing problem," Networks 19 (1989), 731-749. https://doi.org/10.1002/net.3230190702
  2. Berman, P., G. Calinescu, C. Shah, and A. Zelikovsky, "Power efficient monitoring management in sensor networks," Proceedings of IEEE Wireless communication and networking conference, Atlanta, GA, (2004), 2329-2334.
  3. Bertsimas, D. and J. N. Tsitsiklis, Introduction to Linear Optimization, Athena Scientific, Massachusetts, 1997.
  4. Calinescu, G., "A fast localized algorithm for scheduling sensors," Journal of Parallel and Distributed Computing 68 (2006), 507-514.
  5. Cardei, M., M. T. Thai, Y. Li, and W. Wu, "Energy‐efficient target coverage in wireless sensor networks," IEEE INFOCOM 24th Annual Joint Conference of the IEEE Computer and Communications Societies, IEEE Communications Society, Miami, Florida, 3 (2005), 1976-1984.
  6. Cardei, M. and D. Z. Du, "Wireless Sensor Network Lifetime through Power Aware Organization," Wireless Networks 11, 3 (2005), 333-340. https://doi.org/10.1007/s11276-005-6615-6
  7. Cheng, M. X., L. Ruan, and W. Wu, "Coverage Breach Problems in Bandwidth-Constrained Sensor Networks," ACM Transactions on Sensor Networks 3, 12 (2007).
  8. Cheng, M. X. and X. Gong, "Maximum Life Time Coverage Preserving Scheduling Algorithms in Sensor Networks," Journal of Global Optimization, 2010.
  9. Dantzig, G. B. and P. Wolfe, Decomposition principle for linear programs, Operations Research 8, 1 (1960), 101-111. https://doi.org/10.1287/opre.8.1.101
  10. Floreen, P. P. Kaski, T. Musto, and J. Suomela, "Local Approximation Algorithms for Scheduling Problems in Sensor Networks," Lecture Notes in Computer Science 4837 (2008), 99-113.
  11. Ford, L. R. and D. R. Fulkerson, "A suggested computation for maximal multicommodigy network flows," Management Science 5, 1 (1958), 97-101. https://doi.org/10.1287/mnsc.5.1.97
  12. Garey, M. R. and D. S. Johnson, Computers and Intractability: A Guide to the Theory of NP-Completeness, W. H. Freeman and Company, San Francisco, 1979.
  13. Gilmore, P. C. and R. E. Gomory, "A linear programing approach to the cutting‐stock problem," Operations Research 9, 6 (1961), 849-859. https://doi.org/10.1287/opre.9.6.849
  14. Gilmore, P. C. and R. E. Gomory, "A linear programing approach to the cutting‐stock problem-Part II," Operations Research 11, 6 (1963), 863-888. https://doi.org/10.1287/opre.11.6.863
  15. Hahn, R. and H. Reichl, "Batteries and power supplies for wearable and ubiquitous computing," 3rd International Symposium on Wearable Computers, IEEE Computer Society, San Francisco, California, (July/August 1999), 168-169.
  16. Lai, C., C. Ting, and R. Ko, An effective genetic algorithm to improve wireless sensor network lifetime for large-scale surveillance applications, IEEE Congress on Evolutionary Computation, Singapore, (2007), 3531-3538.
  17. Johnson, D. S., M. Yannakakis, and C. H. Papadimitriou, On Generating all Maximal Independent Sets, Information Processing Letters 27 (1988), 119-123. https://doi.org/10.1016/0020-0190(88)90065-8
  18. Lubbecke, M. E. and J. Desrosiers, "Selected topics in column generation," Operations Research 53, 6 (2005), 1007-1023. https://doi.org/10.1287/opre.1050.0234
  19. du Merle, O., D. Villeneuve, J. Desrosiers, and P. Hansen, "Stabilized column generation," Discrete Mathematics 194 (1999), 229-237. https://doi.org/10.1016/S0012-365X(98)00213-1
  20. Marsten, R. E., "The use of the box step method in discrete optimization," Mathematical Programming Study 3 (1975), 127-144.
  21. Marsten, R. E., W. W. Hogan, and J. W. Blankenship, "The BOXSTEP method for large-scale optimization," Operations Research 23, 3 (1975), 389-405. https://doi.org/10.1287/opre.23.3.389
  22. Mito, M. and S. Fujita, "Maximum Connected Domatic Partition of Directed Path Graphs with Single Junction," Lecture Notes in Computer Science 5092 (2008), 425-433.
  23. Moscibroda, T. and R. Wattenhofer, "Maximize the Lifetime of Dominating Sets," IEEE International Parallel and Distributed Processing Symposium, Denver, Colorado, April 2005.
  24. Pemmaraju, S. V. and I. A. Pirwani, "Energy conservation via domatic partitions," 7th ACM international symposium on Mobile ad hoc networking and computing, ACM SIGMOBILE, Florence, Italy, (2006), 143-154.
  25. Pigatti, A., M. P. de Aragao, and E. Uchoa, "Stabilized branch and cut and price for the generalized assignment problem," Electronic Notes in Discrete Mathematics 19 (2005), 389-395.
  26. Slijepcevic, S. and M. Potkonjak, Power efficient organization of wireless sensor networks, IEEE International Conference on Communications, Helsinki, Finland, 2 (2001), 472-476.
  27. Stine, J. and G. de Veciana, Improving energy efficiency of centrally controlled wireless data networks, Wireless Networks 8, 6 (2002), 681-700. https://doi.org/10.1023/A:1020379326558
  28. Wang, B., Coverage Lifetime Maximization in Coverage Control in Sensor Networks, Springer, London, 2010.
  29. Zorbas, D. and C. Douligeris, Satisfying coverage and connectivity in bandwidth constrained sensor networks, 9th International Conference on Communications and information technologies, Incheon, Korea, 2C (2009), 390-395.