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Probabilistic Multi-Tiered Grey Wolf Optimizer-Based Routing for Sustainable Sensor Networks

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 inclina...

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Main Authors: Bahl, Vasudha, Kumar, Anoop
Format: Article
Language:English
Published: Universiti Utara Malaysia Press 2022
Subjects:
QA75 Electronic computers. Computer science
Online Access:https://repo.uum.edu.my/id/eprint/29113/1/JICT%2021%2004%202022%20627-663.pdf
https://repo.uum.edu.my/id/eprint/29113/
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spelling my.uum.repo.291132023-02-02T02:22:44Z https://repo.uum.edu.my/id/eprint/29113/ Probabilistic Multi-Tiered Grey Wolf Optimizer-Based Routing for Sustainable Sensor Networks Bahl, Vasudha Kumar, Anoop QA75 Electronic computers. Computer science 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. Universiti Utara Malaysia Press 2022 Article PeerReviewed application/pdf en cc4_by https://repo.uum.edu.my/id/eprint/29113/1/JICT%2021%2004%202022%20627-663.pdf 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
institution Universiti Utara Malaysia
building UUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Utara Malaysia
content_source UUM Institutional Repository
url_provider http://repo.uum.edu.my/
language English
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Bahl, Vasudha
Kumar, Anoop
Probabilistic Multi-Tiered Grey Wolf Optimizer-Based Routing for Sustainable Sensor Networks
description 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.
format Article
author Bahl, Vasudha
Kumar, Anoop
author_facet Bahl, Vasudha
Kumar, Anoop
author_sort Bahl, Vasudha
title Probabilistic Multi-Tiered Grey Wolf Optimizer-Based Routing for Sustainable Sensor Networks
title_short Probabilistic Multi-Tiered Grey Wolf Optimizer-Based Routing for Sustainable Sensor Networks
title_full Probabilistic Multi-Tiered Grey Wolf Optimizer-Based Routing for Sustainable Sensor Networks
title_fullStr Probabilistic Multi-Tiered Grey Wolf Optimizer-Based Routing for Sustainable Sensor Networks
title_full_unstemmed Probabilistic Multi-Tiered Grey Wolf Optimizer-Based Routing for Sustainable Sensor Networks
title_sort probabilistic multi-tiered grey wolf optimizer-based routing for sustainable sensor networks
publisher Universiti Utara Malaysia Press
publishDate 2022
url https://repo.uum.edu.my/id/eprint/29113/1/JICT%2021%2004%202022%20627-663.pdf
https://repo.uum.edu.my/id/eprint/29113/
_version_ 1756687047928578048
score 13.211869

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