Analysis, modeling and generation of self-similar VBR video traffic
SIGCOMM '94 Proceedings of the conference on Communications architectures, protocols and applications
Modeling and simulation of self-similar variable bit rate compressed video: a unified approach
SIGCOMM '95 Proceedings of the conference on Applications, technologies, architectures, and protocols for computer communication
Experimental queueing analysis with long-range dependent packet traffic
IEEE/ACM Transactions on Networking (TON)
What are the implications of long-range dependence for VBR-video traffic engineering?
IEEE/ACM Transactions on Networking (TON)
On variations of queue response for inputs with the same mean and autocorrelation function
IEEE/ACM Transactions on Networking (TON)
Some noises with spectrum, a bridge between direct current and white noise
IEEE Transactions on Information Theory
The effect of multiple time scales and subexponentiality in MPEG video streams on queueing behavior
IEEE Journal on Selected Areas in Communications
On the use of fractional Brownian motion in the theory of connectionless networks
IEEE Journal on Selected Areas in Communications
IEEE Journal on Selected Areas in Communications
Statistical analysis and simulation study of video teleconference traffic in ATM networks
IEEE Transactions on Circuits and Systems for Video Technology
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Recently it has been reported that variable bit rate (VBR) video traffic exhibits long-range dependence (LRD). Various processes have been proposed for modeling traffic with LRD and analyzing its effects on network performance. However, in the previous models it is not possible to identify the effects of short- and long-term correlation of video traffic on queuing performance, and thus many seemingly contradictory arguments on the importance of LRD in VBR video traffic can be found in the literature. In this paper, we present a video traffic model based on the shifting-level (SL) process. We observe that the autocorrelation function (ACF) of an empirical video trace is accurately captured by a shifting-level process with compound correlation (SLCC): an exponential decay for small lags and a hyperbolic one for large lags. Especially, we present a parameter matching algorithm for video traffic. The continuous-time first-order discrete auto-regressive (C-DAR(1)) model, which is a short-range dependent (SRD) video traffic model, can be considered a kind of SLCC process with an exponential correlation term only. Thus, comparing the queuing performances of the C-DAR(1) model and the SLCC with that of a real video trace, it is possible to identify the effects of SRD and LRD in VBR video traffic on queuing performance. From simulation results, we find that LRD may have a significant effect on queuing behavior under heavy traffic loads and large buffer conditions.