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Application of discrete-time scale invariant systems in video traffic modeling

Although VBR video has been characterized as self-similar by various researchers, models based on self-similarity 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.