• DocumentCode
    2961410
  • Title

    Clustering sensor networks using growing self-organising map

  • Author

    Guru, Siddeswara Mayura ; Hsu, Arthur ; Halgamuge, Saman ; Fernando, Saman

  • Author_Institution
    Mech. & Manuf. Eng., Melbourne Univ., Parkville, Vic., Australia
  • fYear
    2004
  • fDate
    14-17 Dec. 2004
  • Firstpage
    91
  • Lastpage
    96
  • Abstract
    Sensor networks consist of wireless enabled sensor nodes with limited energy. As sensors could be deployed in a large area, data transmitting and receiving are energy consuming operations. One of the methods to save energy is to reduce the transmission distance of each node by grouping nodes into clusters. Each cluster has a cluster-head (CH), which communicates with all the other nodes of that cluster and transmits the data to the remote base station. We describe the adaptation of a growing self-organising map (GSOM) to cluster the wireless sensor nodes and to identify the cluster-heads. We compare the results with a well-known clustering algorithm. We also describe the energy minimization criterion for clustering.
  • Keywords
    data communication; energy conservation; minimisation; power consumption; self-organising feature maps; telecommunication computing; wireless sensor networks; cluster-head; clustering algorithm; data receiving; data transmitting; energy consumption; energy minimization criterion; growing self-organising map; transmission distance; wireless sensor network clustering; Base stations; Clustering algorithms; Energy dissipation; Fasteners; Manufacturing; Mechanical sensors; Milling machines; Power engineering and energy; Strain measurement; Wireless sensor networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Sensors, Sensor Networks and Information Processing Conference, 2004. Proceedings of the 2004
  • Print_ISBN
    0-7803-8894-1
  • Type

    conf

  • DOI
    10.1109/ISSNIP.2004.1417443
  • Filename
    1417443