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Video streaming and conferencing are expected to be the major services in future communication systems. The design of communication systems to support high-quality video services requires the characterisation and modelling of video traffic. An accurate video traffic model for MPEG encoded video traffic proposed. An analysis of MPEG-encoded video traffic shows that I, P and B frame sizes within the same scene are cross-correlated. However, existing frame-level video traffic models often ignore this correlation. In contrast, a new model utilising the multinomial method (MM) is presented to capture this cross-correlation. The MM is used together with the spatial renewal process (SRP) to model MPEG-encoded VBR video traffic. The model is called SRP-MM. In addition the MM is utilised to enhance the existing model, the nested-autoregressive (nested-AR). The enhanced model is called nested-AR-MM. Simulation results demonstrate that the proposed models, the SRP-MM and nested-AR-MM, predict the empirical frame-size marginal distribution, autocorrelation and queuing performance closely. The nested-AR and fractional autoregressive integrated moving average (FARIMA) models from the existing literature are also implemented for comparison. It is shown that the proposed models outperform both nested-AR and FARIMA.
Date of Publication: 7 Oct. 2005