Muhammad Azizi Azizan
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Preferred name
Muhammad Azizi Azizan
Official Name
Muhammad Azizi , Azizan
Alternative Name
Azizan, M. A.
Azizan, Muhammad Azizi
Azizan, Azizi
Azizi Azizan, Muhammad
Azizan, Muhammad Azizi Bin
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Scopus Author ID
57200613794
Researcher ID
IYS-8746-2023

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  • Publication
    X-means clustering for wireless sensor networks
    ( 2020-09-01)
    Radwan A.
    ;
    Kamarudin N.
    ;
    Solihin M.I.
    ;
    Leong H.
    ;
    Rizon M.
    ;
    Hazry Desa
    ;
    Muhammad Azizi Azizan
    K-means clustering algorithms of wireless sensor networks are potential solutions that prolong the network lifetime. However, limitations hamper these algorithms, where they depend on a deterministic K-value and random centroids to cluster their networks. But, a bad choice of the K-value and centroid locations leads to unbalanced clusters, thus unbalanced energy consumption. This paper proposes X-means algorithm as a new clustering technique that overcomes K-means limitations; clusters constructed using tentative centroids called parents in an initial phase. After that, parent centroids split into a range of positions called children, and children compete in a recursive process to construct clusters. Results show that X-means outperformed the traditional K-means algorithm and optimized the energy consumption.
      3