 An energy-efficient cluster formation in wireless sensor network using grey wolf optimisationR. Rajakumar, K. Dinesh and T. Vengattaraman International Journal of Applied Management Science, 2021, vol. 13, issue 2, 124-140 Abstract: With the emerging technology, wireless sensor network (WSNs) plays a vital role in monitoring day-to-day life activities which suffers from various issues such as routing, intrusion, and topology control. However, to address these issues an energy-efficient cluster formation is quite important. Thus, the successive cluster formation improves the lifetime of the networks to reduce routing overheads. Our contribution in this work includes selecting energy-efficient cluster heads with the aid of the Grey Wolf Optimisation (GWO) algorithm. This algorithm attracts several researchers with its efficient leadership capability and hunting methodology but it lags in exploration and exploitation which leads to poor clustering in WSN when it is applied. The proposed methodology includes a tuning parameter for efficient exploration and exploitation later used to solve the issue which resides in WSN. The experimental results show that the proposed algorithm provides better results over cluster head selection and minimised energy consumption in WSN. Keywords: WSN; wireless sensor network; clustering; GWO; grey wolf optimisation; swarm intelligence; exploration; exploitation. (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:ids:injams:v:13:y:2021:i:2:p:124-140 Access Statistics for this article More articles in International Journal of Applied Management Science from Inderscience Enterprises Ltd |
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