Modeling MPEG coded video traffic by Markov-modulated self-similar processes

Document Type

Article

Publication Date

8-1-2001

Abstract

Markov modulated self-similar processes are proposed to model MPEG video sequences that can capture the LRD (Long Range Dependency) characteristics of video ACF (Auto-Correlation Function). The basic idea is to decompose an MPEG compressed video sequence into three parts according to different motion/content complexity such that each part can individually be described by a self-similar process. Beta distribution is used to characterize the marginal cumulative distribution (CDF) of the self-similar process. To model the whole data set, Markov chain is used to govern the transitions among these three self-similar processes. In addition to the analytical derivation, initial simulations have demonstrated that our new model can capture the LRD of ACF and the marginal CDF very well. Network cell loss rate using our proposed synthesized traffic is found to be comparable with that using empirical data as the source traffic.

Identifier

0035425975 (Scopus)

Publication Title

Journal of VLSI Signal Processing Systems for Signal Image and Video Technology

External Full Text Location

https://doi.org/10.1023/A:1011179732518

ISSN

13875485

First Page

101

Last Page

113

Issue

1-2

Volume

29

Fund Ref

State of New Jersey Commission on Science and Technology

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