• DocumentCode
    1851962
  • Title

    Compression scheme for increasing the lifetime of wireless intelligent sensor networks

  • Author

    Sacaleanu, Dragos Ioan ; Stoian, Rodica ; Ofrim, Dragos Mihai ; Deligiannis, Nikos

  • Author_Institution
    Fac. of Electron., Telecommun. & Inf. Technol., Univ. Politeh. din Bucuresti, Bucharest, Romania
  • fYear
    2012
  • fDate
    27-31 Aug. 2012
  • Firstpage
    709
  • Lastpage
    713
  • Abstract
    Wireless intelligent sensor networks (WISN) are characterized by the ability of self-organization and autocoordination for long periods of time. In most cases, the limitation of time function is given by the energy supply of the sensors. Taking into account that the greatest amount of energy is spent in transmission, many studies are concentrated on minimizing the amount of transmitted bits. In order to perform this, data compression algorithms are introduced in data processing. This paper presents a scheme that combines a new extrapolation prediction algorithm and a simple Huffman compression algorithm in order to prolong the lifetime of the WISN. Compared with other data compression schemes, the new scheme has obtained better experimental results in terms of number of bits transmitted and compression ratio.
  • Keywords
    data compression; extrapolation; intelligent sensors; wireless sensor networks; Huffman compression algorithm; WISN lifetime; autocoordination ability; data compression algorithms; data processing; energy supply; extrapolation prediction algorithm; self-organization ability; time function; wireless intelligent sensor networks; Compression algorithms; Data compression; Extrapolation; Heuristic algorithms; Prediction algorithms; Sensors; Wireless sensor networks; Wireless sensor networks; data compression; energy saving; prediction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing Conference (EUSIPCO), 2012 Proceedings of the 20th European
  • Conference_Location
    Bucharest
  • ISSN
    2219-5491
  • Print_ISBN
    978-1-4673-1068-0
  • Type

    conf

  • Filename
    6334057