• DocumentCode
    2332716
  • Title

    Hostile area or facility monitoring with an optimal wireless sensor network deployment

  • Author

    Liu, Jenn-Long ; Lin, Jiann-Horng

  • Author_Institution
    Dept. of Inf. Manage., I-Shou Univ., Kaohsiung, Taiwan
  • fYear
    2010
  • fDate
    18-23 July 2010
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    This study uses an enhanced non-dominated sorting genetic algorithm (enhanced MOGA) to generate the optimal wireless sensor network deployment for monitoring a hostile perimeter area or a critical facility. The sensors are deployed around the area to sense the activities in the area or placed outside the critical facility for sensing the movements of incoming and outgoing of personnel worked in the facility. The distributed sensors are capable of sensing and linking with each other in order to communicate the gathered data via a sensor to a nearby high energy communication node (HECN). The HECN served as a transmission relay to deliver gathered data from the ground to a high-altitude unmanned aerial vehicle (UAV). Two scenarios are implemented by using the enhanced MOGA to achieve the sensor deployment by minimizing the number of sensors and maximizing the coverage. Simulation results will show the Pareto-optimal front, sensor deployment and communication routes between sensors and the HECN.
  • Keywords
    Pareto optimisation; computerised monitoring; condition monitoring; distributed sensors; genetic algorithms; sorting; wireless sensor networks; Pareto optimal front; distributed sensors; enhanced MOGA; enhanced nondominated sorting genetic algorithm; facility monitoring; high altitude unmanned aerial vehicle; high energy communication node; hostile area; optimal wireless sensor network deployment; transmission relay; Base stations; Benchmark testing; Monitoring; Sensors; Sorting; Unmanned aerial vehicles; Wireless sensor networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Evolutionary Computation (CEC), 2010 IEEE Congress on
  • Conference_Location
    Barcelona
  • Print_ISBN
    978-1-4244-6909-3
  • Type

    conf

  • DOI
    10.1109/CEC.2010.5586416
  • Filename
    5586416