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
Recommended Citation
Liu, Hai; Ansari, Nirwan; and Shi, Yun Q., "Markov-modulated self-similar processes: MPEG coded video traffic modeler and synthesizer" (1999). Faculty Publications. 15843.
https://digitalcommons.njit.edu/fac_pubs/15843
