• DocumentCode
    2669436
  • Title

    Optimal location management in mobile computing with hybrid genetic algorithm and particle swarm optimization (GA-PSO)

  • Author

    Wang, Lipo ; Si, Guanglin

  • Author_Institution
    Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore, Singapore
  • fYear
    2010
  • fDate
    12-15 Dec. 2010
  • Firstpage
    1160
  • Lastpage
    1163
  • Abstract
    Location management is an important and complex issue in mobile computing. In the reporting cell location management scheme, the concept of reporting cell was introduced to simplify the management process. As a result, there is a need to optimize the allocation design of reporting cells, since it determines the overall location management cost. We present an approach based on particle swarm optimization (PSO) to obtain minimum cost in the location management problem. Genetic algorithms (GA) are used to improve PSO. Simulation results show that the hybrid algorithm can locate the optimal solution in most cases, within a shorter computational time compared with other algorithms.
  • Keywords
    genetic algorithms; mobile computing; particle swarm optimisation; GA-PSO; cell location management; hybrid genetic algorithm and particle swarm optimization; mobile computing; optimal location management; Gallium; genetic algorithm; location management; mobile computing; particle swarm optimization;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electronics, Circuits, and Systems (ICECS), 2010 17th IEEE International Conference on
  • Conference_Location
    Athens
  • Print_ISBN
    978-1-4244-8155-2
  • Type

    conf

  • DOI
    10.1109/ICECS.2010.5724723
  • Filename
    5724723