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A Local Search Based Approximation Algorithm for Strong Minimum Energy Topology Problem in Wireless Sensor Networks

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7753))

Abstract

Energy-aware network management is extremely important in wireless sensor networks as sensors in the network are powered by battery and it may not be possible to recharge the batteries of sensors after they are deployed. Topology control problem deals with the transmission power assignments to the nodes of a wireless sensor network so that the induced graph topology satisfies some specified properties. Given a set of sensors in the plane, the Strong Minimum Energy Topology (SMET) problem is to assign transmit power to each sensor such that the sum total of powers assigned to all the sensors is minimized subject to the constraint that the induced topology containing only bidirectional links is strongly connected. This will allow the sensors to communicate with each other, while conserving battery power as much as possible leading to increased network life time. So this problem is significant in both theory and application. However, the SMET problem is known to be NP-hard. Several heuristics have been proposed for SMET problem by various researchers. In this paper we propose a local search based heuristic for the SMET problem. We prove that our local search based heuristic is a 2-approximation algorithm. We compare our algorithm with several heuristic algorithms available in the literature. Simulation result shows that the local search based heuristic performs better than the existing heuristics.

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References

  1. Aho, A.V., Hopcroft, J.E., Ullman, J.D.: Data Structures and Algorithms. Addison-Wesley Publishing Company (1987)

    Google Scholar 

  2. Akyildiz, I.F., Su, W., Sankarsubramanian, Y., Cayirci, E.: Wireless Sensor Networks: A Survey. Computer Networks 38, 393–422 (2002)

    Article  Google Scholar 

  3. Aneja, Y.P., Bari, A., Jaekel, A., Chandrasekaran, R., Nair, K.P.K.: Minimum Energy Strong Bidirectional Topology for Ad Hoc Wireless Sensor Networks. In: IEEE ICC Proceedings (2009)

    Google Scholar 

  4. Calinescu, G., Mandoiu, I.I., Zelikovsky, A.: Symmetric Connectivity with Minimum Power Consumption in Radio Networks. In: Proceedings of the IFIP 17th World Computer Congress - TC1 Stream / 2nd IFIP International Conference on Theoretical Computer Science: Foundations of Information Technology in the Era of Networking and Mobile Computing, pp. 119–130 (2002)

    Google Scholar 

  5. Cheng, X., Narahari, B., Simha, R., Cheng, M., Liu, D.: Strong minimum energy topology in wireless sensor networks:NP-Completeness and Heuristics. IEEE Transactions on Mobile Computing 2(3), 248–256 (2003)

    Article  Google Scholar 

  6. Cheng, M.X., Cardei, M., Sun, J., Cheng, X., Wang, L., Xu, Y., Du, D.-Z.: Topology Control of Ad Hoc Wireless Networks for Energy Efficiency. IEEE Transactions on Computers 53(12), 1629–1635 (2004)

    Article  Google Scholar 

  7. Gonzales, T. (ed.): Handbook of Approximation Algorithms and Metaheuristics, ch. 67. Chapman and Hall CRC (2007)

    Google Scholar 

  8. Lu, H.-I., Ravi, R.: The Power of Local Optimization: Approximation Algorithms for Maximum-leaf Spanning Tree. In: Proceedings Thirtieth Annual Allerton Conference on Communication, Control and Computing, pp. 533–542 (1996)

    Google Scholar 

  9. Kirousis, L.M., Kranakis, E., Krizane, D., Pele, A.: Power consumption in packet radio networks. Theoretical Computer Science 243, 289–305 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  10. Labrador, M.A., Wightman, P.M.: Topology Control in Wireless Sensor Networks. Springer (2009)

    Google Scholar 

  11. Lloyd, E.L., Liu, R., Marathe, M.V., Ramanathan, R., Ravi, S.S.: Algorithmic aspects of topology control problems for Ad Hoc Networks, Mobile Networks and Applications 10, 19–34 (2005)

    Google Scholar 

  12. Panda, B.S., Pushparaj Shetty, D.: An Incremental Power Greedy Heuristic for Strong Minimum Energy Topology in Wireless Sensor Networks. In: Natarajan, R., Ojo, A. (eds.) ICDCIT 2011. LNCS, vol. 6536, pp. 187–196. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  13. Ramanathan, R., Rosales-Hain, R.: Topology control of Multihop Wireless Networks using transmit power Adjustment. In: IEEE Infocom (2000)

    Google Scholar 

  14. Rappaport, T.S.: Wireless communications: Principle and Practice. Prentice Hall (1996)

    Google Scholar 

  15. Santi, P.: Topology Control in wireless ad hoc and sensor Networks. ACM Computing Surveys 37(2), 164–194 (2005)

    Article  Google Scholar 

  16. Santi, P.: Topology Control in wireless ad hoc and sensor Networks. Wiley Inter Science (2005)

    Google Scholar 

  17. West, D.B.: Introduction to Graph Theory. PHI (2006)

    Google Scholar 

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Panda, B.S., Shetty, D.P. (2013). A Local Search Based Approximation Algorithm for Strong Minimum Energy Topology Problem in Wireless Sensor Networks. In: Hota, C., Srimani, P.K. (eds) Distributed Computing and Internet Technology. ICDCIT 2013. Lecture Notes in Computer Science, vol 7753. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36071-8_31

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  • DOI: https://doi.org/10.1007/978-3-642-36071-8_31

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-36070-1

  • Online ISBN: 978-3-642-36071-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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