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
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;
Conference_Titel :
Communications, 2006. ICC '06. IEEE International Conference on
Conference_Location :
Istanbul
Print_ISBN :
1-4244-0355-3
Electronic_ISBN :
8164-9547
DOI :
10.1109/ICC.2006.254727