Performance analysis of a multivideo traffic communication network

Raymond Wai-Leung Cheung; Peter C. K. Liu

doi:10.1117/12.251265

16 September 1996 Performance analysis of a multivideo traffic communication network

Raymond Wai-Leung Cheung, Peter C. K. Liu

Proceedings Volume 2952, Digital Compression Technologies and Systems for Video Communications; (1996) https://doi.org/10.1117/12.251265
Event: Advanced Imaging and Network Technologies, 1996, Berlin, Germany

Abstract

In this paper, we investigate a method to find the cell loss probability versus different buffer size for different types of video traffic in a statistical multiplexer. The fluid- flow model has been used to estimate the average cell loss of the video phone traffic. This approach is good for video traffic whose mean and standard variance are small. Conversely, the mean and standard variance for video traffic such as CATV and Studio_TV are comparatively large when those of the video phone traffic are compared. The fluid- flow approach cannot be used in determining the average cell loss probabilities in the video traffic carrying high average mean value because of the unbalancing of the equation roots. Because a motion video source could be represented by a mixture of Gaussian densities and the sequence of coded bit rates can be modeled more accurately by an autoregressive process whose parameters vary in time according to the state of a discrete Markov chain. This implies that the bursty traffic source can be represented by a number of equally virtual sources with relatively small mean and small standard variance. The fluid-flow model works satisfactorily with this virtual source because of its appropriate mean and variance value. When the correlation relationship of these equal virtual sources are properly identified using the discrete-time Markov chain, the result generated by one virtual source can be used to predict the probabilities of total cell loss which could happen to a bursty traffic source. Same technique can be applied to other video traffic whose mean and variance values are comparatively large. Thus, the average cell loss probabilities against different buffer size in a heterogeneous traffic network can be determined.

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Raymond Wai-Leung Cheung and Peter C. K. Liu "Performance analysis of a multivideo traffic communication network", Proc. SPIE 2952, Digital Compression Technologies and Systems for Video Communications, (16 September 1996); https://doi.org/10.1117/12.251265

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KEYWORDS

Video

Autoregressive models

Multiplexers

Differential equations

Motion models

Picosecond phenomena

Statistical analysis

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