• DocumentCode
    3099960
  • Title

    Uneven clustering routing algorithm for Wireless Sensor Networks based on ant colony optimization

  • Author

    Du, Jiang ; Wang, Liang

  • Author_Institution
    Dept. of Comput. Sci. & Technol., Chongqing Univ. of Postd & Telecommun., Chongqing, China
  • Volume
    3
  • fYear
    2011
  • fDate
    11-13 March 2011
  • Firstpage
    67
  • Lastpage
    71
  • Abstract
    In order to make good use of the limited energy, ant colony optimization (ACO) was applied to inter-cluster routing mechanism. An uneven clustering routing algorithm for Wireless Sensor Networks (WSNs) based on ant colony optimization (ACO) was proposed. The algorithm utilized the dynamic adaptability and optimization capabilities of the ant colony to get the optimum route between the cluster head. Meanwhile, it organized different cluter in different size based on the distance between cluster heads and sink node, and clusters closer to sink had smaller sizes than those farther away from the sink, thus the closer cluster heads could preserve energy for the inter-cluster data forwarding. Simulation result indicates that the algorithm effectively balances the network energy consumption and prolongs the network life cycle compared with LEACH and PARA.
  • Keywords
    optimisation; pattern clustering; telecommunication network routing; wireless sensor networks; WSN; ant colony optimization; cluster head; inter-cluster data forwarding; intercluster routing mechanism; network energy consumption; network life cycle; sink node; uneven clustering routing algorithm; wireless sensor networks; Ant colony optimization; Base stations; Clustering algorithms; Energy consumption; Routing; Wireless communication; Wireless sensor networks; Ant Colony Optimization (ACO); energy-effcient; uneven clustring; wireless Sensor Networks (WSNs);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Research and Development (ICCRD), 2011 3rd International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-61284-839-6
  • Type

    conf

  • DOI
    10.1109/ICCRD.2011.5764247
  • Filename
    5764247