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Honey Badger Algorithm Based Clustering with Routing Protocol for Wireless Sensor Networks

K. Arutchelvan1, R. Sathiya Priya1,*, C. Bhuvaneswari2

1 Department of Computer and Information Science, Annamalai University, Chidambaram, Tamilnadu, India
2 Department of Computer Science, Government Arts and Science College, Thiruvennainallur, Tamil Nadu, India

* Corresponding Author: R. Sathiya Priya. Email: email

Intelligent Automation & Soft Computing 2023, 35(3), 3199-3212. https://doi.org/10.32604/iasc.2023.029804

Abstract

Wireless sensor network (WSN) includes a set of self-organizing and homogenous nodes employed for data collection and tracking applications. It comprises a massive set of nodes with restricted energy and processing abilities. Energy dissipation is a major concern involved in the design of WSN. Clustering and routing protocols are considered effective ways to reduce the quantity of energy dissipation using metaheuristic algorithms. In order to design an energy aware cluster-based route planning scheme, this study introduces a novel Honey Badger Based Clustering with African Vulture Optimization based Routing (HBAC-AVOR) protocol for WSN. The presented HBAC-AVOR model mainly aims to cluster the nodes in WSN effectually and organize the routes in an energy-efficient way. The presented HBAC-AVOR model follows a two stage process. At the initial stage, the HBAC technique is exploited to choose an optimal set of cluster heads (CHs) utilizing a fitness function involving many input parameters. Next, the AVOR approach was executed for determining the optimal routes to BS and thereby lengthens the lifetime of WSN. A detailed simulation analysis was executed to highlight the increased outcomes of the HBAC-AVOR protocol. On comparing with existing techniques, the HBAC-AVOR model has outperformed existing techniques with maximum lifetime.

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Cite This Article

K. Arutchelvan, R. S. Priya and C. Bhuvaneswari, "Honey badger algorithm based clustering with routing protocol for wireless sensor networks," Intelligent Automation & Soft Computing, vol. 35, no.3, pp. 3199–3212, 2023.



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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