A novel energy efficient clustering technique based on virtual hexagon for wireless sensor networks

Xin Guan, Lin Guan, Xingang Wang

    Research output: Contribution to journalArticle

    8 Citations (Scopus)

    Abstract

    In the development of wireless sensor networks (WSNs) applications, how to organize sensors into a wireless communication network and route the sensed data from sensors to a remote sink is a particular challenging problem. Therefore, WSNs need a protocol to route data and prolong the lifetime of sensor networks. The clustering technique is an efficient approach for reducing energy consumption in wireless sensor networks. To achieve these purposes, this paper presents a novel clustering algorithm based on virtual hexagon for prolonging lifetime of sensor networks. During the phase of cluster initialization, a sensed zone is divided into several virtual hexagons and the overlapping sensors of circular cluster can be avoided. Furthermore, we make some subcircles in the formatted virtual hexagon based on the average distance between common sensors (non-cluster head sensors) and the cluster's center. Depending on the weight value function, each sensor forms a cluster heads order list. The proposed clustering technique adopts a new method for cluster head election, which can avoid the frequent selection of cluster head. The new clustering algorithm scales well and converges fast for large-scale wireless sensor networks. Simulation results demonstrate that our proposed algorithm is effective in prolonging the lifetime of networks. ICIC International

    Original languageEnglish
    Pages (from-to)1891-1904
    Number of pages14
    JournalInternational Journal of Innovative Computing, Information and Control
    Volume7
    Issue number4
    Publication statusPublished - Apr 2011

    Keywords

    • Cluster
    • Energy efficient
    • Virtual hexagon
    • Wireless sensor networks

    ASJC Scopus subject areas

    • Theoretical Computer Science
    • Software
    • Information Systems
    • Computational Theory and Mathematics

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