• DocumentCode
    237861
  • Title

    Compressive network coding based mobile data gathering technique for Wireless Sensor Networks

  • Author

    Palani, U. ; Alamelu Mangai, V. ; Nachiappan, Alamelu

  • Author_Institution
    Dept. of Electron. & Instrum. Eng., Annamalai Univ., Chidambaram, India
  • fYear
    2014
  • fDate
    8-10 May 2014
  • Firstpage
    951
  • Lastpage
    957
  • Abstract
    WSN consists of a large number of sensor nodes that monitor environmental conditions in a given geographic area. In many of the previous approaches, they have not considered the distance or the hop count during data gathering. This paper proposes the centralized algorithm that places the polling points (PPs) on the shortest path. The shortest path has been obtained through which the data is traversed. The subset of sensors will be selected as polling points that buffer locally aggregated data and upload the data to the mobile collector when it arrives. Then data compression is taking place using compressive Network Coding approach. By simulation results, it is observed that the proposed technique minimizes the energy consumption and delay there by increasing the packet delivery ratio.
  • Keywords
    data compression; network coding; wireless sensor networks; WSN; centralized algorithm; compressive network coding; data compression; delay; energy consumption; environmental conditions monitoring; mobile collector; mobile data gathering technique; packet delivery ratio; polling points; sensor nodes; wireless sensor networks; Area measurement; Computer numerical control; Encoding; Network coding; Numerical models; Wireless communication; Wireless sensor networks; Compressive Network Coding (CNC); Mobile data Collector; Polling Points (PP); Relay hop; Shortest Path tree (SPT); Wireless Sensor Network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Communication Control and Computing Technologies (ICACCCT), 2014 International Conference on
  • Conference_Location
    Ramanathapuram
  • Print_ISBN
    978-1-4799-3913-8
  • Type

    conf

  • DOI
    10.1109/ICACCCT.2014.7019234
  • Filename
    7019234