Bahl, Vasudha and Kumar, Anoop (2022) Probabilistic Multi-Tiered Grey Wolf Optimizer-Based Routing for Sustainable Sensor Networks. Journal of Information and Communication Technology, 21 (4). pp. 627-663. ISSN 2180-3862

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Abstract

Wireless sensor networks (WSN) have a wide range of applications. Therefore, developing an energy-efficient methodology for estimating cluster heads (CHs) to ensure efficient data transmission has become highly relevant. Meta-heuristic strategies for optimal CHs are the current investigation inclination. As the network grows, the conventional optimization strategies emerge unsuccessful, and the outcomes of hybridizing bring performance enhancement in WSN. A Probabilistic Multi-Tiered Grey Wolf Optimizer (GWO) was implemented in this study on an upgraded Grey Wolf Optimizer for optimum CH selection. It used fitness value to strengthen GWO’s search for the best solution, resulting in even dispersal of CHs. Communication routes were updated based on routes to the CHs and base station to lessen energy consumption by a layered-based routing scheme. GWO’s governance enhanced the network’s ability. The distributed nodes’ geographical territory was categorized into four tiers. CH was chosen grounded on the objective value that required fewer difficult control factors than existing techniques. Simulations showed that the suggested technique could extend the network’s stability time by (31.5 %) compared to hetDEEC-3, L-DDRI, Novel-LEACH-POS, DBSCDS-GWO, and P-SEP.

Item Type:	Article
Uncontrolled Keywords:	Cluster head, energy optimization, grey wolf optimization, cluster head selection, wireless sensor network lifespan
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:	School of Computing
Depositing User:	Mrs Nurin Jazlina Hamid
Date Deposited:	24 Jan 2023 06:17
Last Modified:	02 Feb 2023 02:22
URI:	https://repo.uum.edu.my/id/eprint/29113

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