• DocumentCode
    149742
  • Title

    Data aggregation in wireless sensor networks: Compressing or forecasting?

  • Author

    Jin Cui ; Valois, Fabrice

  • Author_Institution
    INSA-Lyon, Univ. de Lyon, Villeurbanne, France
  • fYear
    2014
  • fDate
    6-9 April 2014
  • Firstpage
    2892
  • Lastpage
    2897
  • Abstract
    Data aggregation is a key problem in wireless sensor networks due to both energy-constrained and bandwidth-constrained. In this paper, we highlight the aggregation benefits in network layer and MAC layer by modeling the energy consumption for some energy-efficient routing protocols and MAC protocols. Besides, we define two parameters, aggregation ratio w and packet size coefficient λ, to evaluate the efficiency of an aggregation method, and we discuss their trade-off. Additionally, we propose comparison between A-ARMA and compressive sensing, which are on behalf of the state-of-the-art forecasting aggregation and compressing aggregation respectively.
  • Keywords
    access protocols; autoregressive moving average processes; compressed sensing; routing protocols; telecommunication power management; wireless sensor networks; A-ARMA; MAC layer; MAC protocol; adaptive auto regression moving average; aggregation ratio; bandwidth constrain; compressing aggregation; compressive sensing; data aggregation; energy constrain; energy consumption; energy-efficient routing protocol; network layer; packet size coefficient; state-of-the-art forecasting aggregation; wireless sensor network; Correlation; Energy consumption; Media Access Protocol; Routing; Routing protocols; Wireless sensor networks; compressive sensing; data aggregation; temporal series; wireless sensor network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Wireless Communications and Networking Conference (WCNC), 2014 IEEE
  • Conference_Location
    Istanbul
  • Type

    conf

  • DOI
    10.1109/WCNC.2014.6952909
  • Filename
    6952909