Markov-modulated self-similar processes: MPEG coded video traffic modeler and synthesizer

Document Type

Conference Proceeding

Publication Date

12-1-1999

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). An MPEG compressed video sequence is decomposed into three parts according to different motion/change complexity such that each part can individually be described by a self-similar process. Beta distribution is used to characterize the marginal cumulative distribution function (CDF) of each self-similar processes, and Markov chain is used to govern the transition among these three self-similar processes. Network cell loss rate using our proposed synthesized traffic is found to be comparable with that using empirical data as the source traffic.

Identifier

0033293499 (Scopus)

Publication Title

Conference Record IEEE Global Telecommunications Conference

First Page

1184

Last Page

1188

Volume

2

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