• DocumentCode
    592215
  • Title

    Maximum lifetime strategy for target monitoring in a mobile sensor network with obstacles

  • Author

    Masoudimansour, W. ; Mahboubi, Hamid ; Aghdam, Amir G. ; Sayrafian-Pour, Kamran

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Concordia Univ., Montréal, QC, Canada
  • fYear
    2012
  • fDate
    10-13 Dec. 2012
  • Firstpage
    1404
  • Lastpage
    1410
  • Abstract
    In this paper, an energy efficient technique is proposed for target monitoring in a mobile sensor network in the presence of obstacles. The main sources of energy consumption in a mobile sensor are sensing, communicating and movement. The objective is to maximize the lifetime of the network while monitoring the target. To this end, a graph is constructed and its edges are weighted according to the remaining energy of each sensor. The lifetime maximization problem is subsequently transformed into a shortest-path problem. The proposed technique provides an efficient relocation strategy for the sensors and an energy-efficient route to transfer information from the target to the destination in the presence of obstacles. It is shown that under certain conditions, the lifetime of the network under the proposed strategy is close to the maximum achievable time. Simulations demonstrate the effectiveness of the proposed technique.
  • Keywords
    distributed sensors; energy conservation; energy consumption; graph theory; network theory (graphs); object detection; target tracking; telecommunication network reliability; telecommunication power management; wireless sensor networks; edge weighing; efficient relocation strategy; energy consumption; energy efficient technique; energy-efficient information transfer route; graph construction; lifetime maximization problem; maximum lifetime strategy; mobile sensor network; shortest-path problem; target monitoring; Energy consumption; Mobile communication; Mobile computing; Monitoring; Robot sensing systems; Target tracking;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Decision and Control (CDC), 2012 IEEE 51st Annual Conference on
  • Conference_Location
    Maui, HI
  • ISSN
    0743-1546
  • Print_ISBN
    978-1-4673-2065-8
  • Electronic_ISBN
    0743-1546
  • Type

    conf

  • DOI
    10.1109/CDC.2012.6425902
  • Filename
    6425902