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An Energy-Efficient Cluster Head Selection Using Artificial Bees Colony Optimization for Wireless Sensor Networks

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Abstract

In a cluster-based Wireless Sensor Networks (WSN) , dividing the network into clusters and choosing an efficient Cluster Head (CH) is a big issue. The selection of CH is a very challenging task, and it affects the energy consumption of the network and also the lifetime of sensors and ultimately network lifetime. This chapter presents a new approach for CH selection based on Artificial Bee Colony (ABC) optimization. This ABC optimization is based upon the remaining energy, intra-cluster distance , and distance from the sink station. The fitness function for ABC is calculated based on three parameters, i.e., residual energy ; distance from the sink station; and intra-cluster distance. We optimized the fitness function using ABC optimization. The objective of optimizing the fitness function is to select an optimal CH for each cluster which reduces the energy consumption of the WSN. The proposed model is analyzed through extensive experiments and the outcomes are compared with some famous existing approaches.

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Correspondence to Tauseef Ahmad .

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Ahmad, T., Haque, M., Khan, A.M. (2019). An Energy-Efficient Cluster Head Selection Using Artificial Bees Colony Optimization for Wireless Sensor Networks. In: Shandilya, S., Shandilya, S., Nagar, A. (eds) Advances in Nature-Inspired Computing and Applications. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-319-96451-5_8

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  • DOI: https://doi.org/10.1007/978-3-319-96451-5_8

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