• DocumentCode
    3441234
  • Title

    An efficient energy data gathering based on grid-chain for wireless sensor networks

  • Author

    Yung-Fa Huang ; Li-Chu Yang ; Jen-Yung Lin

  • Author_Institution
    Dept. of Inf. & Commun. Eng., Chaoyang Univ. of Technol., Taichung, Taiwan
  • fYear
    2012
  • fDate
    21-24 Aug. 2012
  • Firstpage
    78
  • Lastpage
    82
  • Abstract
    Energy efficiency and network life time prolonging are the important issues for data gathering in wireless sensor network (WSN). In this paper, we propose an energy efficient grid-chain based data gathering (EEGDG) method, which can effectively improve the above two problems based on the chain by combining the grid architecture with clustering. The proposed EEGDG divides the sensing area into several sub-areas, and uses the concept of cluster to choose one node in each area for sensing data and data gathering. Thus, to reduce the transmission energy the chain distance is minimized to improve the disadvantages of chain hop and prolonging the network life time. Simulation results show that the proposed EEGDG can prolong the network life time and reduce the node energy consumption to a large degree.
  • Keywords
    pattern clustering; telecommunication network reliability; wireless sensor networks; EEGDG method; WSN; chain distance; energy efficient grid-chain based data gathering method; grid architecture-clustering; network lifetime prolonging; node energy consumption; transmission energy; wireless sensor networks; Base stations; Brain modeling; Computer architecture; Energy consumption; Energy efficiency; Sensors; Wireless sensor networks; energy efficiency; formatting; grid-chain; network life time; wireless sensor network (WSN);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Awareness Science and Technology (iCAST), 2012 4th International Conference on
  • Conference_Location
    Seoul
  • Print_ISBN
    978-1-4673-2111-2
  • Electronic_ISBN
    978-1-4673-2110-5
  • Type

    conf

  • DOI
    10.1109/iCAwST.2012.6469593
  • Filename
    6469593