Title :
Markov-modulated self-similar processes: MPEG coded video traffic modeler and synthesizer
Author :
Liu, Hai ; Ansari, Nzrwan ; Shi, Yun Q.
Author_Institution :
Dept. of Electr. & Comput. Eng., New Jersey Inst. of Technol., Newark, NJ, USA
fDate :
6/21/1905 12:00:00 AM
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
Keywords :
Markov processes; computational complexity; image sequences; telecommunication traffic; video coding; ACF; CDF; LRD characteristics; MPEG coded video traffic modeler; MPEG compressed video sequence; Markov-modulated self-similar processes; auto-correlation function; beta distribution; change complexity; long range dependency; marginal cumulative distribution function; motion complexity; network cell loss rate; source traffic; synthesized traffic; synthesizer; Autocorrelation; Communication system traffic control; Distribution functions; Statistical distributions; Synthesizers; Telecommunication traffic; Traffic control; Transform coding; Video compression; Video sequences;
Conference_Titel :
Global Telecommunications Conference, 1999. GLOBECOM '99
Conference_Location :
Rio de Janeireo
Print_ISBN :
0-7803-5796-5
DOI :
10.1109/GLOCOM.1999.829959
