Abstract
Wireless Sensor Networks consist of wide range of applications to be discerned and researched nowadays. The foremost restraint of these Networks is to reduce energy consumption and to prolong the lifetime of the network. In this paper a meta-heuristic optimization technique, Cuckoo Search is used to aggregate data in the Sensor Network. In the proposed technique, the least energy nodes are formed as subordinate chains (or) clusters for sensing the data and high energy nodes as Cluster Head for communicating to the base station. The Cuckoo search is proposed to get enhanced network performance incorporating balanced energy dissipation and results in the formation of optimum number of clusters and minimal energy consumption. The feasibility of the scheme is manifested by the Simulation results on comparison with the traditional methods.
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Akyildiz, I.F., Su, W., Sankarasubramaniam, Y., Cayirci, E.: Wireless Sensor Net-works: a survey. Computer Networks 38, 393–422 (2002)
Akojwar, A.G., Patrikar, R.M.: Improving Life Time of Wireless Sensor Networks Using Neural Network Based Classification Techniques with Cooperative Routing. International Journal of Communications 2(1), 75–86 (2008)
Chakraborty, W., Chakraborty, A., Mitra, S.K., Naskar, M.K.: An Energy Effi-cient scheme for data gathering in Wireless Sensor networks using Particle Swarm optimization. Journal of Applied Computer Science 6(3), 9–13 (2009)
Yang, X., Deb, S.: Cuckoo Search via Levy flights. Paper Presented at the Proc. of World Congress on Nature & Biologically Inspired Computing, (Nabic), pp. 210–214. IEEE, India (2009)
Heinzelman, W., Chandrakasan, A., Balakrishnan, H.: An application-specific Protocol architecture for wireless microsensor networks. IEEE Transactions on Wireless Communications, 660–670 (2002)
Younis, O., Fahmy, S.: HEED: a hybrid, energy-efficient, distributed Clustering approach for ad hoc sensor networks. Transactions on Mobile Computing 3, 660–669 (2004)
Sundarambal, M., Dhivya, M., Anbalagan, P.: Performance evaluation of Bandwidth Allocation in ATM networks. Inderscience, International Journal of Business In-formation Systems 6(3), 398–417 (2010)
Aslam, N., Phillips, W., Robertson, W.: A Unified Clustering and Communication Protocol for Wireless Sensor Networks. IAENG International Journal of Computer Science 35(3), http://www.iaeng.org/IJCS/issues_v35/issue_3/IJCS_35_3_01.pdf
Dhivya, M., Sundarambal, M., Anand, L.N.: Energy Efficient Computation Of Data Fusion in Wireless Sensor Networks Using Cuckoo Based Particle Approach (CBPA). Int. J. Communications, Network and System Sciences (April 2011), doi:10.4236/ijcns.2011.44030
Yang, X.-S., Deb, S.: Engineering optimization by cuckoo search. Int. J. Mathematical Modelling and Numerical Optimization 1(4), 330–343 (2010)
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Dhivya, M., Sundarambal, M., Vincent, J.O. (2011). Energy Efficient Cluster Formation in Wireless Sensor Networks Using Cuckoo Search. In: Panigrahi, B.K., Suganthan, P.N., Das, S., Satapathy, S.C. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2011. Lecture Notes in Computer Science, vol 7077. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27242-4_17
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DOI: https://doi.org/10.1007/978-3-642-27242-4_17
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-27241-7
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