• DocumentCode
    2982821
  • Title

    Multi-objective Network Coding Optimization Based on NSGA-II Algorithm

  • Author

    Kun Hao ; Beibei Wang ; Yongmei Luo

  • Author_Institution
    Sch. of Comput. & Inf. Eng., Tianjin Inst. of Urban Constr., Tianjin, China
  • fYear
    2012
  • fDate
    7-9 Dec. 2012
  • Firstpage
    843
  • Lastpage
    846
  • Abstract
    Network coding could effectively improve transmission performance of multicast network, but encoding of node brings the additional calculation cost of node. In order to overcome the overhead brought by network coding, a network coding optimization model under the framework of algebraic network coding is designed in this paper, and the joint optimization for both the link cost and coding cost of network coding are carried out based on this model. In addition, the paper proposes MOONC (Multi-Objective Optimization Problem of Network Coding) based on improved NSGA-II algorithm. Adopting non-dominated sorting mechanism, virtual fitness and elitist strategy, this algorithm could not only improve algorithm efficiency and convergence speed, but also guarantee the population diversity. The simulation for typical network topology shows that this algorithm is effective and feasible.
  • Keywords
    genetic algorithms; multicast communication; network coding; MOONC; NSGA-II algorithm; algebraic network coding; elitist strategy; encoding; joint optimization; multicast network; multiobjective network coding optimization; multiobjective optimization problem; network coding optimization model; network topology; nondominated sorting genetic algorithm; sorting mechanism; transmission performance improvement; virtual fitness; Algorithm design and analysis; Encoding; Network coding; Optimization; Sociology; Statistics; Vectors; Coding Cost; Link Cost; NSGA-II Algorithm; Network Coding;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control Engineering and Communication Technology (ICCECT), 2012 International Conference on
  • Conference_Location
    Liaoning
  • Print_ISBN
    978-1-4673-4499-9
  • Type

    conf

  • DOI
    10.1109/ICCECT.2012.21
  • Filename
    6413765