K-Means and Fuzzy based Hybrid Clustering Algorithm for WSN

• Autorzy: Angadi Basavaraj M. , Kakkasageri Mahabaleshwar S.

Identyfikatory

DOI

10.24425/ijet.2023.147703

• Języki publikacji: EN

Abstrakty

EN

Wireless Sensor Networks (WSN) acquired a lot of attention due to their widespread use in monitoring hostile environments, critical surveillance and security applications. In these applications, usage of wireless terminals also has grown significantly. Grouping of Sensor Nodes (SN) is called clustering and these sensor nodes are burdened by the exchange of messages caused due to successive and recurring re-clustering, which results in power loss. Since most of the SNs are fitted with nonrechargeable batteries, currently researchers have been concentrating their efforts on enhancing the longevity of these nodes. For battery constrained WSN concerns, the clustering mechanism has emerged as a desirable subject since it is predominantly good at conserving the resources especially energy for network activities. This proposed work addresses the problem of load balancing and Cluster Head (CH) selection in cluster with minimum energy expenditure. So here, we propose hybrid method in which cluster formation is done using unsupervised machine learning based kmeans algorithm and Fuzzy-logic approach for CH selection.

Słowa kluczowe

EN

wireless sensor networks; cluster; K-Means algorithm; fuzzy logic

• Wydawca: Polish Academy of Sciences, Committee of Electronics and Telecommunication
• Czasopismo: International Journal of Electronics and Telecommunications
• Rocznik: 2023
• Tom: Vol. 69, No. 4
• Strony: 793--801
• Opis fizyczny: Bibliogr. 24 poz., rys., tab., wykr.

Twórcy

autor

Angadi Basavaraj M.

• Faculty of Electronics and Communication Engineering Department,Basaveshwar Engineering College, Bagalkote, Karnataka, INDIA

autor

Kakkasageri Mahabaleshwar S.

• Faculty of Electronics and Communication Engineering Department,Basaveshwar Engineering College, Bagalkote, Karnataka, INDIA

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).