• DocumentCode
    2635099
  • Title

    Double cluster-heads clustering algorithm for wireless sensor networks using PSO

  • Author

    Ruihua, Zhang ; Zhiping, Jia ; Xin, Li ; Dongxue, Han

  • Author_Institution
    Sch. of Comput. Sci. & Technol., Shandong Univ., Jinan, China
  • fYear
    2011
  • fDate
    21-23 June 2011
  • Firstpage
    763
  • Lastpage
    766
  • Abstract
    One of the most important design criteria for wireless sensor networks (WSNs) is energy efficiency. Clustering provides an effective way for extending the lifetime of the network. In this paper, we propose a double cluster-heads clustering algorithm using particle swarm optimization (PSO-DH). The algorithm generates two cluster heads. The election of the master cluster-head and the vice cluster-head needs consider the state information, including location and energy reserved about nodes and their neighbors. The Master Cluster Head (MCH) receives and aggregates the data from its member nodes. The aggregation data are sent to the vice one. The Vice Cluster Head (VCH) transmits aggregation data to the sink directly. This algorithm can balance the energy consumption, so it can extend the network lifetime effectively. Simulation results show the lifetime of the algorithm is extended for 50% contrast with LEACH.
  • Keywords
    energy conservation; particle swarm optimisation; pattern clustering; wireless sensor networks; data aggregation; double cluster-heads clustering algorithm; energy consumption; energy efficiency; master cluster head; member nodes; particle swarm optimization; vice cluster head; wireless sensor networks; Clustering algorithms; Conferences; Energy consumption; Integrated circuit modeling; Particle swarm optimization; Protocols; Wireless sensor networks; clustering; double cluster-heads; particle swarm optimization; wireless sensor network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Electronics and Applications (ICIEA), 2011 6th IEEE Conference on
  • Conference_Location
    Beijing
  • ISSN
    pending
  • Print_ISBN
    978-1-4244-8754-7
  • Electronic_ISBN
    pending
  • Type

    conf

  • DOI
    10.1109/ICIEA.2011.5975688
  • Filename
    5975688