# ARSH-FATI a novel metaheuristic for cluster head selection in wireless sensor networks

journal contribution
posted on 28.07.2021, 23:29 authored by Haider Ali, Mubashir Hussain, Liu Lu, John Panneerselvam, Xiaojun Zhai
IEEE Wireless sensor network (WSN) consists of a large number of sensor nodes distributed over a certain target area. The WSN plays a vital role in surveillance, advanced healthcare, and commercialized industrial automation. Enhancing energy-efficiency of the WSN is a prime concern because higher energy consumption restricts the lifetime (LT) of the network. Clustering is a powerful technique widely adopted to increase LT of the network and reduce the transmission energy consumption. In this article (LT) we develop a novel ARSH-FATI-based Cluster Head Selection (ARSH-FATI-CHS) algorithm integrated with a heuristic called novel ranked-based clustering (NRC) to reduce the communication energy consumption of the sensor nodes while efficiently enhancing LT of the network. Unlike other population-based algorithms ARSH-FATI-CHS dynamically switches between exploration and exploitation of the search process during run-time to achieve higher performance trade-off and significantly increase LT of the network. ARSH-FATI-CHS considers the residual energy, communication distance parameters, and workload during cluster heads (CHs) selection. We simulate our proposed ARSH-FATI-CHS and generate various results to determine the performance of the WSN in terms of LT. We compare our results with state-of-the-art particle swarm optimization (PSO) and prove that ARSH-FATI-CHS approach improves the LT of the network by $\sim \text{25}\%$.

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2386

2397

12

1937-9234

1932-8184

IEEE

Yes

No

28/03/2020

## External Author Affiliations

University of Leicester, University of Derby, University of New South Wales; University of Essex, UK

Yes

## Journal

IEEE Systems Journal

## Exports

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