• DocumentCode
    2469125
  • Title

    Reducing energy consumption in human-centric wireless sensor networks

  • Author

    Meseguer, Roc ; Molina, Carlos ; Ochoa, Sergio F. ; Santos, Rodrigo

  • Author_Institution
    Dept. of Comput. Archit., Univ. Politec. de Catalunya, Barcelona, Spain
  • fYear
    2012
  • fDate
    14-17 Oct. 2012
  • Firstpage
    1473
  • Lastpage
    1478
  • Abstract
    Energy consumption is a main research issue in wireless sensor networks; and particularly in those where nodes collaborate to reach a goal. This article explores the energy consumption in mobile devices participating in a human-based wireless sensor network. Specifically, the paper proposes the use of a message predictor to help detect and reduce the number of unnecessary control packets delivered by the nodes as a way to keep updated the network topology. In order to evaluate this proposal, the Optimized Link State Routing protocol was modified to add a message predictor between the routing and the network layers. Eleven simulations were performed using a particular setting. The preliminary results indicate the use of the message predictor can help reduce considerably the nodes energy consumption without affecting the routing capability of the protocol. Although these results are still preliminary, they are highly encouraging.
  • Keywords
    mobile handsets; routing protocols; telecommunication network topology; wireless sensor networks; energy consumption reduction; human-centric wireless sensor networks; message predictor; mobile devices; network topology; optimized link state routing protocol; unnecessary control packet; Energy consumption; Mobile handsets; Network topology; Routing; Routing protocols; Wireless sensor networks; energy consumption; human-centric wireless sensor network; messages prediction; opportunistic network;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics (SMC), 2012 IEEE International Conference on
  • Conference_Location
    Seoul
  • Print_ISBN
    978-1-4673-1713-9
  • Electronic_ISBN
    978-1-4673-1712-2
  • Type

    conf

  • DOI
    10.1109/ICSMC.2012.6377943
  • Filename
    6377943