Hybridization of Optimization Algorithm-Based Trust Aware Clustering Scheme for Wireless Sensor Networks

International Journal of Electronics and Communication Engineering

© 2023 by SSRG - IJECE Journal

Volume 10 Issue 9

Year of Publication : 2023

Authors : Deena Sivakumar, S. Suganthi Devi, T. Nalini

10.14445/23488549/IJECE-V10I9P103

How to Cite?

Deena Sivakumar, S. Suganthi Devi, T. Nalini, "Hybridization of Optimization Algorithm-Based Trust Aware Clustering Scheme for Wireless Sensor Networks," SSRG International Journal of Electronics and Communication Engineering, vol. 10,  no. 9, pp. 20-27, 2023. Crossref, https://doi.org/10.14445/23488549/IJECE-V10I9P103

Abstract:

Energy optimization is the most open problem in WSN. Most of the work concentrates on clustering approaches for reducing energy consumption and improving the stability period. The sensor networks include sensor nodes with restricted battery levels to monitor physical events at several locations. Data collecting is an archetypal but vital function in several Wireless Sensor Networks (WSN) applications. It can be essential to continuously operate the sensor network in an energyeffective system to collect data. This study presents a novel Hybrid Glowworm Search Optimization based Trust Aware Clustering Scheme (HGSO-TACS) technique for WSN. The presented HGSO-TACS technique aims to accomplish secure cluster communication with trust metrics. In addition, the HGSO model is designed by integrating the GSO model with Lens Oppositional Based Learning (LOBL). Moreover, the proposed HGSO-TACS method computes an objective function with multiple parameters in the network. The experimental validation of the HGSO-TACS method can be carried out under various features. The relative study revealed the improvements of the HGSO-TACS technique over other current approaches.

Keywords:

Clustering, Stability, Trust, Wireless Sensor Networks, Stability, Energy efficiency.

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