• DocumentCode
    3452144
  • Title

    Energy efficient head node selection algorithm in wireless sensor networks

  • Author

    Chen, Wanming ; Meng, Max Q -H ; Li, Shuai ; Mei, Tao ; Liang, Huawei ; Li, Yangming

  • Author_Institution
    Inst. of Intell. Machines, Chinese Acad. of Sci., Hefei
  • fYear
    2007
  • fDate
    15-18 Dec. 2007
  • Firstpage
    1366
  • Lastpage
    1371
  • Abstract
    Energy problem is a key issue for the wireless sensor network with limited batteries. It´s a good idea to select a head node for data aggregation to save the energy of data transmitting. However, many algorithms don´t consider the whole integrated network situation for head node selection. We proposed an energy efficient head node selection method for data aggregation. In this algorithm, three aspects were taken into consideration, which were the candidate head node´s single residual energy, the total energy spent in the network if this candidate head node is chosen, and the quality of balance of the residual nodes´ energy. To adapt the actual sensor nodes with limited memory and computing capacity, a simplified model is also introduced. Simulation results show that this new head node selection algorithm can achieve balanced energy consumption and prolong the life time of the network highly.
  • Keywords
    wireless sensor networks; balanced energy consumption; data aggregation; data transmission; energy efficient head node selection algorithm; energy saving; head node selection; integrated network situation; residual energy; wireless sensor networks; Batteries; Biomimetics; Clustering algorithms; Energy efficiency; Intelligent networks; Magnetic heads; Relays; Robot sensing systems; Robotics and automation; Wireless sensor networks; Wireless sensor networks; data aggregation; head node selection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Robotics and Biomimetics, 2007. ROBIO 2007. IEEE International Conference on
  • Conference_Location
    Sanya
  • Print_ISBN
    978-1-4244-1761-2
  • Electronic_ISBN
    978-1-4244-1758-2
  • Type

    conf

  • DOI
    10.1109/ROBIO.2007.4522363
  • Filename
    4522363