• DocumentCode
    2099712
  • Title

    An Improved Multiple Objectives Optimization of QoS Routing Algorithm Base on Genetic Algorithm

  • Author

    Wang Xueshun ; Yu Shao-hua ; Luo Ting ; Dai JinYou

  • Author_Institution
    Huazhong Univ. of Sci. & Technol., Wuhan, China
  • fYear
    2009
  • fDate
    24-26 Sept. 2009
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Providing quality of service (QoS) guarantees in packet networks gives rise to several challenging issues. One of them is how to determine a feasible path that satisfies a set of constraints. Multi-constrained QoS routing finds a feasible route in the network that satisfies multiple independent constraints. In general, multi-constrained path selection is a NP-complete problem that cannot be exactly solved in polynomial time. The existing routing algorithms usually optimize a single objective, which have some inherent drawbacks. An improved genetic algorithm based on multi-objective optimization algorithm for multiple QoS routing constraints is proposed in this paper, which search for the set of Pareto optimal solutions of QoS routing. Simulation results show that this algorithm has a high success ratio, and can obtain a set of QoS routing which satisfy all constraints in finite evolutionary generations. Those Qos routing overcomes the drawbacks of single objective optimization.
  • Keywords
    computational complexity; genetic algorithms; quality of service; telecommunication network routing; NP-complete problem; Pareto optimal solutions; QoS routing algorithm; finite evolutionary generations; genetic algorithm; improved multiple objectives optimization; quality of service; Constraint optimization; Delay; Genetic algorithms; Jitter; NP-complete problem; Pareto optimization; Polynomials; Protocols; Quality of service; Routing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Wireless Communications, Networking and Mobile Computing, 2009. WiCom '09. 5th International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-3692-7
  • Electronic_ISBN
    978-1-4244-3693-4
  • Type

    conf

  • DOI
    10.1109/WICOM.2009.5302038
  • Filename
    5302038