• DocumentCode
    2204987
  • Title

    A nature-inspired algorithm for intelligent optimization of network resources

  • Author

    Feng, Xiang ; Lau, Francis C M ; Shuai, Dianxun

  • Author_Institution
    Dept. of Comput. Sci., East China Univ. of Sci. & Technol., Shanghai, China
  • fYear
    2008
  • fDate
    19-21 Nov. 2008
  • Firstpage
    284
  • Lastpage
    288
  • Abstract
    In complex computer networks having the characteristic of social dynamics, bandwidth allocation is a fundamental problem where bandwidth has to be reserved for connections in advance. This paper presents the theory and approach of the economic generalized particle model (EGPM) for intelligent allocation of network bandwidth. This approach transforms the complicated network bandwidth allocation problem into efficient, parallel allocation of network bandwidth. This approach is an important extension and further development of the generalized particle model (GPM) [1]. EGPM emphasizes the use of pricing as the network control mechanism. For the pricing, it makes use of the tatonnement process in economics. EGPM arises from GPM but can overcome some of GPM¿s deficiencies for the network bandwidth allocation problem.
  • Keywords
    bandwidth allocation; computer networks; iterative methods; pricing; bandwidth allocation; computer networks; economic generalized particle model; intelligent optimization; network bandwidth; network resources; Bandwidth; Channel allocation; Computer networks; Computer science; Environmental economics; Feedback; Intelligent networks; Parallel algorithms; Pricing; Quality of service; Intelligent bandwidth allocation; distributed and parallel algorithm; dynamical process; economic generalized particle model (EGPM); price and demands dynamic modulation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communication Systems, 2008. ICCS 2008. 11th IEEE Singapore International Conference on
  • Conference_Location
    Guangzhou
  • Print_ISBN
    978-1-4244-2423-8
  • Electronic_ISBN
    978-1-4244-2424-5
  • Type

    conf

  • DOI
    10.1109/ICCS.2008.4737189
  • Filename
    4737189