A histogram-based model for video traffic behavior in an ATM multiplexer
IEEE/ACM Transactions on Networking (TON)
Wide-area traffic: the failure of Poisson modeling
SIGCOMM '94 Proceedings of the conference on Communications architectures, protocols and applications
Analysis, modeling and generation of self-similar VBR video traffic
SIGCOMM '94 Proceedings of the conference on Communications architectures, protocols and applications
Source models for VBR broadcast-video traffic
IEEE/ACM Transactions on Networking (TON)
Conference proceedings on Applications, technologies, architectures, and protocols for computer communications
IEEE/ACM Transactions on Networking (TON)
The GBAR source model for VBR videoconferences
IEEE/ACM Transactions on Networking (TON)
Modeling full-length VBR video using Markov-renewal-modulated TES models
IEEE Journal on Selected Areas in Communications
Modeling video traffic using M/G/∞ input processes: a compromise between Markovian and LRD models
IEEE Journal on Selected Areas in Communications
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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 processes. 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.