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Cluster head selection using hesitant fuzzy and firefly algorithm in wireless sensor networks

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Abstract

Nowadays, wireless sensor networks (WSNs) are used to monitor and collect data in various environments. One of the main challenges in WSNs is the energy consumption due to the deployed sensor nodes in WSNs are energy-constrained. Clustering method is a solution for this problem and the cluster head (CH) selection process is a major part of the clustering method. This paper used the firefly algorithm (FA) and hesitant fuzzy to propose a new CH selection protocol. The proposed protocol uses three parameters of sensor nodes to calculate the score of each node to determine the best CHs. In order to describe the performance of the proposed protocol, three scenarios are simulated and evaluated. The simulation results show that the proposed protocol improves the energy saving and increases the network lifetime.

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Authors and Affiliations

  1. Department of Computer Science, Faculty of Mathematics and Computer, Shahid Bahonar University of Kerman, Kerman, Iran

    Mojgan Rayenizadeh & Marjan Kuchaki Rafsanjani

  2. Department of Pure Mathematics, Faculty of Mathematics and Computer, Shahid Bahonar University of Kerman, Kerman, Iran

    Arsham Borumand Saeid

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  1. Mojgan Rayenizadeh
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  2. Marjan Kuchaki Rafsanjani
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  3. Arsham Borumand Saeid
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Correspondence to Arsham Borumand Saeid.

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Rayenizadeh, M., Kuchaki Rafsanjani, M. & Borumand Saeid, A. Cluster head selection using hesitant fuzzy and firefly algorithm in wireless sensor networks. Evolving Systems 13, 65–84 (2022). https://doi.org/10.1007/s12530-021-09405-1

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