Statistical analysis and simulation study of video teleconference traffic in ATM networks

Heyman, Daniel P.; Tabatabai, A.; Lakshman, T. V.

doi:10.1109/76.134371

Cited by 411 publications

(76 citation statements)

References 8 publications

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“…The DAR(p) process, constructed and analyzed by Jacobs and Lewis (1978), has developed into one of several standard tools for modelling input traffic in telecommunication networks. Elwalid et al (1995) and Heyman et al (1992) analyzed several traces of variable-bit-rate videoconferencing traffic and modelled them using the DAR(1) process. Ryu and Elwalid (1996) used the DAR(p) process to accurately model video traffic.…”

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confidence: 99%

Mean queue size in a queue with discrete autoregressive arrivals of order p

Kim

Kim²,

Sohraby

2008

Ann Oper Res

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We consider a discrete time single server queueing system where the arrival process is governed by a discrete autoregressive process of order p (DAR(p)), and the service time of a customer is one slot. For this queueing system, we give an expression for the mean queue size, which yields upper and lower bounds for the mean queue size. Further we propose two approximation methods for the mean queue size. One is based on the matrix analytic method and the other is based on simulation. We show, by illustrations, that the proposed approximations are very accurate and computationally efficient.

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confidence: 99%

Mean queue size in a queue with discrete autoregressive arrivals of order p

Kim

Kim²,

Sohraby

2008

Ann Oper Res

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“…They also studied modeling of broadcast video using Gamma, Weibull and Pareto distributions. Heyman et al [18] applied Markov chain models to videoconference sequences coded using DPCM/DCT and VBR schemes and showed that they can accurately estimate cell loss rate. Krunz et al [14] have studied the frame size distribution for each frame type of a MPEG encoded sequence.…”

Section: Introductionmentioning

confidence: 99%

<title>Application of discrete-time scale invariant systems in video traffic modeling</title>

Narasimha

Rao

2002

SPIE Proceedings

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Although VBR video has been characterized as self-similar by various researchers, models based on selfsimilarity considerations have not been previously studied. This paper investigates the application of discrete-time scale invariant systems to modeling variable-bit rate (VBR) video traces. The motivation for this study lies in the fact that the model discussed here evolves out of self-similarity considerations. Potential application of this system to classifying content-based scenes in VBR video is explored. This paper also demonstrates that using heavy-tailed stable inputs these models can match both the scene time-series correlations as well as scene density functions.

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“…The DAR(p) process, constructed and analyzed by Jacobs and Lewis [12], has developed into one of several standard tools for modelling input traffic in telecommunication networks. Elwalid et al [6] and Heyman et al [9] analyzed several traces of variable-bit-rate videoconferencing traffic and modelled them using the DAR(1) process. Ryu and Elwalid [19] used the DAR(p) process to accurately model video traffic.…”

Section: Introductionmentioning

confidence: 99%

Regularly varying tails in a queue with discrete autoregressive arrivals of order p

Kim

2007

Queueing Syst

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We consider a discrete time single server queueing system where the service time of a customer is one slot, and the arrival process is governed by a discrete autoregressive process of order p (DAR(p)). For this queueing system, we investigate the tail behavior of the queue size and the waiting time distributions. Specifically, we show that if the stationary distribution of DAR(p) input has a tail of regular variation with index −β −1, then the stationary distributions of the queue size and the waiting time have tails of regular variation with index −β.

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Statistical analysis and simulation study of video teleconference traffic in ATM networks

Cited by 411 publications

References 8 publications

Mean queue size in a queue with discrete autoregressive arrivals of order p

Mean queue size in a queue with discrete autoregressive arrivals of order p

<title>Application of discrete-time scale invariant systems in video traffic modeling</title>

Regularly varying tails in a queue with discrete autoregressive arrivals of order p

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