Proceedings of the 2006 international conference on Wireless communications and mobile computing
VBR video traffic modeling and synthetic data generation using GA-optimized Volterra filters
International Journal of Network Management
A comparison of AR full motion video traffic models in B-ISDN
Computers and Electrical Engineering
A unified traffic model for MPEG-4 and H.264 video traces
IEEE Transactions on Multimedia
Detection of multiple changes in fractional integrated ARMA processes
IEEE Transactions on Signal Processing
AR-based quadratic modeling for GOP MPEG-encoded video traffic in ATM networks
Computer Communications
Joint source and sending rate modeling in adaptive video streaming
Image Communication
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This paper presents a new traffic model for MPEG-encoded video sequences. The hybrid gamma/Pareto distribution is used for all three types of frames in MPEG-encoded video sequences, and the present model takes scene changes into account. The autocorrelation structure is modeled using two second-order auto-regressive (AR) processes nested with each other. One AR process is used to generate the mean frame size of the scenes to model the long-range dependence, and another AR process is used to generate the fluctuations within the scenes to model the short range dependence. The parameters of the AR processes are estimated from measurements of empirical video sequences. Simulation results show that the present model captures the autocorrelation structure in the empirical traces at both small and large lags. The MPEG traffic model presented in this paper is used to predict the queueing performance of single and multiplexed MPEG video sequences at an asynchronous transfer mode multiplexer. Comparison study shows that the present model provides accurate prediction for quality of service measures, such as cell-loss ratio under different traffic loads and various buffer sizes