Abstract
Clustering of sensor nodes is an energy efficient approach to extend lifetime of wireless sensor networks. It organizes the sensor nodes in independent clusters. Clustering of sensor nodes avoids the long distance communication of nodes and hence prolongs the network functioning time. The number of cluster heads is an important aspect for energy efficient clustering of nodes because total intra-cluster communication distance and total distance of cluster heads to base station depends upon number of cluster heads. In this paper, we have used genetic algorithms for optimizing the number of cluster heads while taking trade-off between total intra-cluster distance and total distance of cluster heads to base station. Experimental results show that proposed scheme can efficiently optimize the number of cluster heads for clustering of nodes in wireless sensor networks.
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References
Akyildiz, I., Su, W., Sankarasubramaniam, Y., Cayirci, E.: Wireless sensor networks: a survey. Comput. Netw. 38(4), 393–422 (2002)
Estrin, D., Govindan, R., Heidemann, J.S., Kumar, S.: Next century challenges: scalable coordination in sensor networks. In: MOBICOM. pp. 263–270 (1999)
Younis, O., Krunz, M., Ramasubramanian, S.: Node clustering in wireless sensor networks: recent developments and deployment challenges. IEEE Network Mag. 20, 2025 (2006)
Abbasi, A.A., Younis, M.: A survey on clustering algorithms for wireless sensor networks. Comput. Commun. 30(14–15), 2826–2841 (2007)
Karl, H., Willig, A.: Protocols and Architectures for Wireless Sensor Networks. Wiley, England (2007)
Heinzelman, W.R., Chandrakasan, A., Balakrishnan, H.: Energy efficient communication protocol for wireless microsensor networks. In: Proceedings of the 33rd Hawaii International Conference on System Sciences, pp. 10–20 (2000)
Heinzelman, W., Chandrakasan, A., Balakrishnan, H.: An application-specific protocol architecture for wireless microsensor networks. IEEE Trans. Wireless Commun. 1(4), 660–670 (2002)
Murata, T., Ishibuchi, H.: Performance evaluation of genetic algorithms for fowshop scheduling problems. In: Proceeding First IEEE Conference on IEEE World Congress on Computational Intelligence, Evolutionary Computation, pp. 812–817 (1994)
Bajaber, F., Awan, I.: Adaptive decentralized re-clustering protocol for wireless sensor networks. J. Comput. Syst. Sci. 77(2), 282292 (2011)
Heidari, E., Movaghar, A.: An efficient method based on genetic algorithms to solve sensor network optimization problem. Int J. GRAPH-HOC 3(1), 18–32 (2011)
Sajid, H., Abdul, W.M., Obidul, I.: Genetic algorithm for hierachical wireless sensor networks. J. Netw. 2(5), 87–97 (2007)
Jin, F., Parish, D.J.: Using a genetic algorithm to optimize the performance of a wireless sensor network. In: Proceeding PGNet, (2007)
Jenn-Long, L., Chinya, V.R.: LEACH-GA: genetic algorithm-based energy-efficient adaptive clustering protocol for wireless sensor networks. Int. J. Mach. Learn. Comput. 1(1), 79–85 (2011)
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Pal, V., Singh, G., Yadav, R.P. (2014). Optimizing Number of Cluster Heads in Wireless Sensor Networks for Clustering Algorithms. In: Babu, B., et al. Proceedings of the Second International Conference on Soft Computing for Problem Solving (SocProS 2012), December 28-30, 2012. Advances in Intelligent Systems and Computing, vol 236. Springer, New Delhi. https://doi.org/10.1007/978-81-322-1602-5_132
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DOI: https://doi.org/10.1007/978-81-322-1602-5_132
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