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MODELING VBR VIDEO TRAFFIC BY MARKOV-MODULATED SELF-SIMILAR PROCESSES

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

It is estimated that video traffic will be increasingly occupying a major portion of future network bandwidth, and thus traffic modeling plays an important role for network design and management. In this paper., we propose Markov modulated self-similar processes to model MPEG video sequences that can capture the LRD (long range dependency) characteristics of video ACF (auto-correlation function). The basic idea behind this modeling is to decompose an MPEG compressed video sequence into three parts according to different motion/change complexity. Each part can individually be described by a self-similar process. In addition, Beta distribution is used to characterize the marginal cumulative distribution (CDF) of the video traffic. To model the whole data set, Markov chain is used as a dominating process to govern the tr,ansitions among these three self-similar processes. Initial simulations on a real MPEG compressed movie sequence of Star Wars have demonstrated that our new model can capture the LRD of ACF and the marginal CDF very well. Video traffic synthesis using our model is presented. Further research in this direction is discussed.

Original languageEnglish (US)
Title of host publication1999 IEEE 3rd Workshop on Multimedia Signal Processing
EditorsK.J. Ray Liu, Jorn Ostermann, Ed Deprettere, W. Bastiaan Kleijn, John Aasted Sorensen
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages363-368
Number of pages6
ISBN (Electronic)0780356101, 9780780356108
DOIs
StatePublished - 1999
Event3rd IEEE Workshop on Multimedia Signal Processing, MMSP 1999 - Copenhagen, Denmark
Duration: Sep 13 1999Sep 15 1999

Publication series

Name1999 IEEE 3rd Workshop on Multimedia Signal Processing

Conference

Conference3rd IEEE Workshop on Multimedia Signal Processing, MMSP 1999
Country/TerritoryDenmark
CityCopenhagen
Period9/13/999/15/99

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Media Technology

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