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Enhancing energy efficiency and reliability in wireless sensor networks using BioGAT optimization

Dublin Core		PKP Metadata Items	Metadata for this Document
1.	Title	Title of document	Enhancing energy efficiency and reliability in wireless sensor networks using BioGAT optimization
2.	Creator	Author's name, affiliation, country	D. K. Shareef; Mohan Babu University (Erstwhile Sree Vidyanikethan Engineering College (Autonomous)); India
2.	Creator	Author's name, affiliation, country	Veeramreddy Jyothsna; Mohan Babu University (Erstwhile Sree Vidyanikethan Engineering College (Autonomous)); India
3.	Subject	Discipline(s)	Computer and Informatics
3.	Subject	Keyword(s)	BioGAT model; Biogeography-based; Energy efficiency; Network reliability; Node placement; Optimization; Wireless sensor networks
4.	Description	Abstract	The BioGAT model, as proposed, presents a novel methodology for enhancing the efficiency of wireless sensor networks (WSNs), which are essential elements of contemporary communication and sensing systems. For real-time monitoring and data analysis, WSNs are comprised of autonomous sensor nodes that are outfitted with processing, wireless communication, and sensing capabilities. These nodes are deployed in a variety of environments. By means of an advanced optimization model, this work aims to address critical challenges in WSNs, specifically in the areas of node placement, energy efficiency, and network reliability. By utilizing biogeography-based optimization (BBO) and graph attention networks (GAT), the BioGAT model endeavors to dynamically adapt to network changes while achieving a balance between efficient coverage and energy consumption. Cluster heads (CHs), which are essential for the aggregation of data, have a significant impact on improvements in energy efficiency and the longevity of networks. By means of comprehensive simulations and evaluation, this study presents exceptional outcomes. The BioGAT model outperforms prior approaches by attaining a 95% packet delivery ratio and an enhanced throughput. In addition, the model effectively decreases mean energy consumption, underscoring its capacity to improve the sustainability and dependability of networks in a variety of WSN applications.
5.	Publisher	Organizing agency, location	Institute of Advanced Engineering and Science
6.	Contributor	Sponsor(s)
7.	Date	(YYYY-MM-DD)	2025-01-01
8.	Type	Status & genre	Peer-reviewed Article
8.	Type	Type
9.	Format	File format	PDF
10.	Identifier	Uniform Resource Identifier	https://ijeecs.iaescore.com/index.php/IJEECS/article/view/38205
10.	Identifier	Digital Object Identifier (DOI)	http://doi.org/10.11591/ijeecs.v37.i1.pp601-612
11.	Source	Title; vol., no. (year)	Indonesian Journal of Electrical Engineering and Computer Science; Vol 37, No 1: January 2025
12.	Language	English=en	en
14.	Coverage	Geo-spatial location, chronological period, research sample (gender, age, etc.)
15.	Rights	Copyright and permissions	Copyright (c) 2024 SHAREEF D K This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.