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Erschienen in: Wireless Networks 8/2019

27.08.2019

An energy efficient stable clustering approach using fuzzy extended grey wolf optimization algorithm for WSNs

verfasst von: Nitin Mittal, Urvinder Singh, Rohit Salgotra, Balwinder Singh Sohi

Erschienen in: Wireless Networks | Ausgabe 8/2019

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Abstract

Wireless sensor network (WSN) is a cost-effective networking solution for information updating in the coverage radius or in the sensing region. To record a real-time event, a large number of sensor nodes (SNs) need to be arranged systematically, such that information collection is possible for a longer span of time. But, the hurdle faced by WSN is the limited resources of SNs. Hence, there is a high demand to design and implement an energy-efficient scheme to prolong the performance parameters of WSN. Clustering-based routing is the most suitable approach to support for load balancing, fault tolerance, and reliable communication to prolong performance parameters of WSN. These performance parameters are achieved at the cost of reduced lifetime of cluster head (CH). To overcome such limitations in clustering based hierarchical approach, efficient CH selection algorithm, and optimized routing algorithm are essential to design efficient solution for larger scale networks. In this paper, fuzzy extended grey wolf optimization algorithm based threshold-sensitive energy-efficient clustering protocol is proposed to prolong the stability period of the network. Analysis and simulation results show that the proposed algorithm significantly outperforms competitive clustering algorithms in the context of energy consumption, stability period and system lifetime.

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Metadaten
Titel
An energy efficient stable clustering approach using fuzzy extended grey wolf optimization algorithm for WSNs
verfasst von
Nitin Mittal
Urvinder Singh
Rohit Salgotra
Balwinder Singh Sohi
Publikationsdatum
27.08.2019
Verlag
Springer US
Erschienen in
Wireless Networks / Ausgabe 8/2019
Print ISSN: 1022-0038
Elektronische ISSN: 1572-8196
DOI
https://doi.org/10.1007/s11276-019-02123-2

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