Open Access

ARTICLE

Energy Aware Seagull Optimization-Based Unequal Clustering Technique in WSN Communication

by D. Anuradha^1,*, R. Srinivasan², T. Ch. Anil Kumar³, J. Faritha Banu⁴, Aditya Kumar Singh Pundir⁵, D. Vijendra Babu⁶

1 Department of Computer Science and Engineering, Panimalar Engineering College, Chennai, 600 123, India
2 Department of Computer Science and Engineering, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai, 600 062, India
3 Department of Mechanical Engineering, Vignan’s Foundation for Science Technology and Research, Guntur, 522213, India
4 Department of Computer Science and Engineering, SRM Institute of Science and Technology, Ramapuram, Chennai, 600 089, India
5 Department of Electronics and Communication Engineering, Arya College of Engineering and Information Technology, Jaipur, 302 028, India
6 Department of Electronics and Communication Engineering, Aarupadai Veedu Institute of Technology, Vinayaka Mission’s Research Foundation, Paiyanoor, 603 104, India

* Corresponding Author: D. Anuradha. Email:

Intelligent Automation & Soft Computing 2022, 32(3), 1325-1341. https://doi.org/10.32604/iasc.2022.021946

Received 21 July 2021; Accepted 02 September 2021; Issue published 09 December 2021

Abstract

Wireless sensor network (WSN) becomes a hot research area owing to an extensive set of applications. In order to accomplish energy efficiency in WSN, most of the earlier works have focused on the clustering process which enables to elect CHs and organize unequal clusters. However, the clustering process results in hot spot problem and can be addressed by the use of unequal clustering techniques, which enables to construct of clusters of unequal sizes to equalize the energy dissipation in the WSN. Unequal clustering can be formulated as an NP-hard issue and can be solved by metaheuristic optimization algorithms. With this motivation, this paper presents a novel seagull optimization (SGO) based unequal clustering (SGOBUC) model to attain energy efficiency in WSN. The SGO algorithm is mainly inspired by the migrating and attacking behaviour of seagulls. They are formulated in a mathematical way and designed to highlight exploration as well as exploitation in a provided searching area. The SGOBUC technique derives a fitness involving different parameters in such a way that energy efficiency can be accomplished. A comprehensive simulation analysis takes place to showcase the enhanced outcomes of the SGOBUC technique. The simulation outcomes highlighted the betterment of the SGOBUC technique over the recent techniques interms of different dimensions.

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Keywords

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