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Erschienen in:
Automatic Generation of Cyber Architectures Optimized for Security, Cost, and Mission Performance: A Nature-Inspired Approach Kapitel lesen Erstes Kapitel lesen

2019 | OriginalPaper | Buchkapitel

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

verfasst von : Tauseef Ahmad, Misbahul Haque, Asad Mohammad Khan

Erschienen in: Advances in Nature-Inspired Computing and Applications

Verlag: Springer International Publishing

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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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Vorheriges Kapitel A Comparison of Bio-Inspired Approaches for the Cluster-Head Selection Problem in WSN
Nächstes Kapitel Modified Krill Herd Algorithm for Global Numerical Optimization Problems
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Metadaten
Titel
An Energy-Efficient Cluster Head Selection Using Artificial Bees Colony Optimization for Wireless Sensor Networks
verfasst von
Tauseef Ahmad
Misbahul Haque
Asad Mohammad Khan
Copyright-Jahr
2019
Buch
Advances in Nature-Inspired Computing and Applications

Print ISBN: 978-3-319-96450-8

Electronic ISBN: 978-3-319-96451-5

Copyright-Jahr: 2019

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

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