Using Hybrid Genetic Algorithm for Data Aggregation in Wireless Sensor Networks

Using Hybrid Genetic Algorithm for Data Aggregation in Wireless Sensor Networks

Efficient energy usage is vital for extending Wireless Sensor Networks (WSNs) lifespan. While Improved LowEnergy Adaptive Clustering Hierarchy (ILEACH) excels in energy-efficient data aggregation, challenges like premature cluster head (CH) failure remain. Genetic Algorithm (GA) optimizes parameters...

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Published in:Proceedings of the 2024 18th International Conference on Ubiquitous Information Management and Communication, IMCOM 2024
Main Author: Sharmin S.; Ahmedy I.; Noor R.M.; Ismail H.
Format: Conference paper
Language:English
Published: Institute of Electrical and Electronics Engineers Inc. 2024
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85186145788&doi=10.1109%2fIMCOM60618.2024.10418358&partnerID=40&md5=9932f4fd34372481da6a9a33e86324e0
id 2-s2.0-85186145788
spelling 2-s2.0-85186145788
Sharmin S.; Ahmedy I.; Noor R.M.; Ismail H.
Using Hybrid Genetic Algorithm for Data Aggregation in Wireless Sensor Networks
2024
Proceedings of the 2024 18th International Conference on Ubiquitous Information Management and Communication, IMCOM 2024


10.1109/IMCOM60618.2024.10418358
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85186145788&doi=10.1109%2fIMCOM60618.2024.10418358&partnerID=40&md5=9932f4fd34372481da6a9a33e86324e0
Efficient energy usage is vital for extending Wireless Sensor Networks (WSNs) lifespan. While Improved LowEnergy Adaptive Clustering Hierarchy (ILEACH) excels in energy-efficient data aggregation, challenges like premature cluster head (CH) failure remain. Genetic Algorithm (GA) optimizes parameters, including energy, in WSNs. We propose a novel hybrid ILEACH-GA algorithm for data aggregation. ILEACH forms clusters, GA evaluates fitness, selecting optimal clusters for aggregation. GA mitigates ILEACH's premature CH failure. ILEACH-GA surpasses LEACH, ILEACH, and GA-LEACH, with significantly higher throughput (10.0%, 47.4%, 21.9 respectively), retaining higher residual energy (0.0805) and alive nodes (25.5%). This innovation boosts sustainable WSN data aggregation, overcoming limitations, and enhancing performance. This innovation elevates sustainable WSN data aggregation, surmounting limitations, and augmenting performance, applicable in waste and crop management systems. © 2024 IEEE.
Institute of Electrical and Electronics Engineers Inc.

English
Conference paper
author Sharmin S.; Ahmedy I.; Noor R.M.; Ismail H.
spellingShingle Sharmin S.; Ahmedy I.; Noor R.M.; Ismail H.
Using Hybrid Genetic Algorithm for Data Aggregation in Wireless Sensor Networks
author_facet Sharmin S.; Ahmedy I.; Noor R.M.; Ismail H.
author_sort Sharmin S.; Ahmedy I.; Noor R.M.; Ismail H.
title Using Hybrid Genetic Algorithm for Data Aggregation in Wireless Sensor Networks
title_short Using Hybrid Genetic Algorithm for Data Aggregation in Wireless Sensor Networks
title_full Using Hybrid Genetic Algorithm for Data Aggregation in Wireless Sensor Networks
title_fullStr Using Hybrid Genetic Algorithm for Data Aggregation in Wireless Sensor Networks
title_full_unstemmed Using Hybrid Genetic Algorithm for Data Aggregation in Wireless Sensor Networks
title_sort Using Hybrid Genetic Algorithm for Data Aggregation in Wireless Sensor Networks
publishDate 2024
container_title Proceedings of the 2024 18th International Conference on Ubiquitous Information Management and Communication, IMCOM 2024
container_volume
container_issue
doi_str_mv 10.1109/IMCOM60618.2024.10418358
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85186145788&doi=10.1109%2fIMCOM60618.2024.10418358&partnerID=40&md5=9932f4fd34372481da6a9a33e86324e0
description Efficient energy usage is vital for extending Wireless Sensor Networks (WSNs) lifespan. While Improved LowEnergy Adaptive Clustering Hierarchy (ILEACH) excels in energy-efficient data aggregation, challenges like premature cluster head (CH) failure remain. Genetic Algorithm (GA) optimizes parameters, including energy, in WSNs. We propose a novel hybrid ILEACH-GA algorithm for data aggregation. ILEACH forms clusters, GA evaluates fitness, selecting optimal clusters for aggregation. GA mitigates ILEACH's premature CH failure. ILEACH-GA surpasses LEACH, ILEACH, and GA-LEACH, with significantly higher throughput (10.0%, 47.4%, 21.9 respectively), retaining higher residual energy (0.0805) and alive nodes (25.5%). This innovation boosts sustainable WSN data aggregation, overcoming limitations, and enhancing performance. This innovation elevates sustainable WSN data aggregation, surmounting limitations, and augmenting performance, applicable in waste and crop management systems. © 2024 IEEE.
publisher Institute of Electrical and Electronics Engineers Inc.
issn
language English
format Conference paper
accesstype
record_format scopus
collection Scopus
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