• DocumentCode
    2835855
  • Title

    A Recursive Algorithm for Gamma Mixture Models

  • Author

    Almhana, J. ; Liu, Z. ; Choulakian, V. ; McGorman, R.

  • Author_Institution
    University of Moncton, Moncton, New Brunswick, Canada E1A 3E9. almhanaj@umoncton.ca
  • Volume
    1
  • fYear
    2006
  • fDate
    38869
  • Firstpage
    197
  • Lastpage
    202
  • Abstract
    The hyper-Erlang model can approximate any non-negative distribution as closely as desired. It can not only characterize field data well, but also facilitate analytically tractable results for performance evaluation. As a result, this model is widely used in telecommunication network modeling. This paper proposes an online algorithm for Gamma mixture distributions, which contain hyper-Erlang models as a special case, and applies the algorithm to Internet traffic modeling. Simulation and experimental results are also provided.
  • Keywords
    Bandwidth; Density functional theory; IP networks; Internet; Iterative algorithms; Pattern analysis; Performance analysis; Quality of service; Telecommunication traffic; Traffic control; EM algorithm; Internet traffic; Mixture Gamma distribution; hyper-Erlang distribution;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communications, 2006. ICC '06. IEEE International Conference on
  • Conference_Location
    Istanbul
  • ISSN
    8164-9547
  • Print_ISBN
    1-4244-0355-3
  • Electronic_ISBN
    8164-9547
  • Type

    conf

  • DOI
    10.1109/ICC.2006.254727
  • Filename
    4024117