Wavelet and Time-Domain Modeling of Multi-Layer VBR Video Traffic

Modeling of video traffic has always been an important research area for the design, simulation, and performance analysis of packet video networks and Internet streaming. In this paper, we present a frame-level hybrid framework for modeling multi-layer VBR video traffic, in which the base layer is modeled using a combination of wavelet and time-domain methods and the enhancement layer is linearly predicted from the basedlayer model. To accurately capture long-range dependent (LRD) and short-range dependent (SRD) properties of VBR base-layer traffic, we use wavelets to model the distribution of I-frame sizes and a simple time-domain model for P/B frame sizes; however, unlike previous studies, we analyze and successfully model both inter-GOP and intra-GOP correlation found in many VBR sequences. Through the use of QQ plots and leaky-bucket simulations, we demonstrate that our model not only effectively preserves the temporal burstiness of the original traffic, but also captures important statistical features of the original video such as the autocorrelation function and the frame-size distribution. We also show that our model performs better than the previous methods in single-layer and multi-layer MPEG-4 sequences and demonstrate that certain results obtained in prior work for MPEG-1 video do not hold for general GOP-based coding schemes.