• DocumentCode
    2711967
  • Title

    QoS Parameter Optimization Using Multi-Objective Genetic Algorithm in MANETs

  • Author

    Asraf, Noor M. ; Ainon, Raja N. ; Keong, Phang Keat

  • Author_Institution
    Fac. of Comput. Sci. & Inf. Technol., Univ. of Malaya, Kuala Lumpur, Malaysia
  • fYear
    2010
  • fDate
    26-28 May 2010
  • Firstpage
    138
  • Lastpage
    143
  • Abstract
    The increase in proliferation of mobile devices and wireless technologies in recent years has opened up new challenges in mobile ad hoc networks (MANET). This growth has also led to an increase in demand of applications such as streaming video, multi-player interactive games and financial services such as real-time stock quotes. Such applications impose a strict guarantee on quality of service (QoS), namely on end-to-end delay, bandwidth consumption and cost. But finding a path that satisfies multiple constraints is inherently hard. Further challenges occur with routing in a mobile environment where nodes are mobile, the data delivery path constantly changes and routing is constrained by battery levels. Multicast routing can improve network usage by sharing resources when sending messages to multiple destinations especially when multiple mobile nodes are located within transmission range of a node. We propose a multicast routing technique based on multi-objective genetic algorithm (MOGA) that optimizes multiple QoS parameters in MANET to find an optimal multicast tree. Simulation studies show that the GA is robust and scales well for a relatively large number of nodes.
  • Keywords
    Bandwidth; Batteries; Costs; Delay; Games; Genetic algorithms; Mobile ad hoc networks; Quality of service; Routing; Streaming media; Genetic Algorithm; QoS optimization; multicast routing; traffic engineering;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Mathematical/Analytical Modelling and Computer Simulation (AMS), 2010 Fourth Asia International Conference on
  • Conference_Location
    Kota Kinabalu, Malaysia
  • Print_ISBN
    978-1-4244-7196-6
  • Type

    conf

  • DOI
    10.1109/AMS.2010.40
  • Filename
    5489640