Statistical division based modeling for multimedia network traffic

Author

Li, Baibing ; De Moor, Bart

Author_Institution

Dept. of Electr. Eng., Katholieke Univ., Leuven, Belgium

Volume

1

fYear

1999

fDate

1999

Firstpage

27

Abstract

For Markov modulated Poisson process (MMPP) models, a statistical division (SD) based modeling approach is proposed for multimedia network traffic. Due to its exploiting information from observed data, the SD can make significant reductions of problem-scales and then lead to a fast algorithm in comparison with the previously proposed non-informed division (NID) approach (reduced to 5.84% of the CPU time in the practical case given in this paper). Thus, modeling of MMPP can be largely speeded up to trace multimedia network traffic

Keywords

Markov processes; Poisson distribution; modelling; multimedia communication; statistical analysis; telecommunication traffic; time-domain analysis; Markov modulated Poisson process models; fast algorithm; multimedia network traffic; statistical division based modeling; Communication system traffic control; Computer networks; Distribution functions; Large-scale systems; Parameter estimation; Signal processing algorithms; Stochastic processes; Streaming media; Telecommunication traffic; Traffic control;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing and Its Applications, 1999. ISSPA '99. Proceedings of the Fifth International Symposium on

Conference_Location

Brisbane, Qld.

Print_ISBN

1-86435-451-8

Type

conf

DOI

10.1109/ISSPA.1999.818104

Filename

818104