An intelligent algorithm for energy efficiency optimization in software-defined wireless sensor networks for 5G communications

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dc.authoridNalbant, Kemal Gokhan/0000-0002-5065-2504
dc.contributor.authorGokhan Nalbant, Kemal
dc.contributor.authorAlsuhibany, Suliman A.
dc.contributor.authorHassan Alshehri, Asma
dc.contributor.authorHatira, Maha
dc.contributor.authorChoi, Bong Jun
dc.date.accessioned2025-03-09T10:48:43Z
dc.date.available2025-03-09T10:48:43Z
dc.date.issued2024
dc.departmentİstanbul Beykent Üniversitesi
dc.description.abstractWireless communications have lately experienced substantial exploitation because they provide a lot of flexibility for data delivery. It provides connection and mobility by using air as a medium. Wireless sensor networks (WSN) are now the most popular wireless technologies. They need a communication infrastructure that is both energy and computationally efficient, which is made feasible by developing the best communication protocol algorithms. The internet of things (IoT) paradigm is anticipated to be heavily reliant on a networking architecture that is currently in development and dubbed software-defined WSN. Energy-efficient routing design is a key objective for WSNs. Cluster routing is one of the most commonly used routing techniques for extending network life. This research proposes a novel approach for increasing the energy effectiveness and longevity of software-defined WSNs. The major goal is to reduce the energy consumption of the cluster routing protocol using the firefly algorithm and high-efficiency entropy. According to the findings of the simulation, the suggested method outperforms existing algorithms in terms of system performance under various operating conditions. The number of alive nodes determined by the proposed algorithm is about 42.06% higher than Distributed Energy-Efficient Clustering with firefly algorithm (DEEC-FA) and 13.95% higher than Improved Firefly Clustering IFCEER and 12.05% higher than another referenced algorithm.
dc.description.sponsorshipMSIT Korea under the NRF Korea [NRF- 2022R1A2C4001270]; Innovative Human Resource Development for Local Intellectualization support program [IITP-2023-RS-2022-00156360]
dc.description.sponsorshipThis research was supported by the MSIT Korea under the NRF Korea (NRF- 2022R1A2C4001270) and the Innovative Human Resource Development for Local Intellectualization support program (IITP-2023-RS-2022-00156360) supervised by the IITP.
dc.identifier.doi10.1371/journal.pone.0301078
dc.identifier.issn1932-6203
dc.identifier.issue6
dc.identifier.pmid38900762
dc.identifier.scopus2-s2.0-85196559710
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1371/journal.pone.0301078
dc.identifier.urihttps://hdl.handle.net/20.500.12662/4649
dc.identifier.volume19
dc.identifier.wosWOS:001281810400006
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.language.isoen
dc.publisherPublic Library Science
dc.relation.ispartofPlos One
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_WOS_20250310
dc.titleAn intelligent algorithm for energy efficiency optimization in software-defined wireless sensor networks for 5G communications
dc.typeArticle

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