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TES Modeling of Video Traffic
Benjamin MELAMED Bhaskar SENGUPTA
IEICE TRANSACTIONS on Communications
Publication Date: 1992/12/25
Print ISSN: 0916-8516
Type of Manuscript: Special Section PAPER (Special Issue on Teletraffic)
modeling and simulation, software systems, TES processes, stochastic processes, autocorrelation function, autocorrelated processes, video modeling,
Full Text: PDF(854KB)>>
Video service is slated to be a major application of emerging high-speed communications networks of the future. In particular, full-motion video is designed to take advantage of the high bandwidths that will become affordably available with the advent of B-ISDN. A salient feature of compressed video sources is that they give rise to autocorrelated traffic streams, which are difficult to model with traditional modeling techniques. In this paper, we describe a new methodology, called TES (Transform-Expand-Sample) , for modeling general autocorrelated time series, and we apply it to traffic modeling of compressed video. The main characteristic of this methodology is that it can model an arbitrary marginal distribution and approximate the autocorrelation structure of an empirical sample such as traffic measurements. Furthermore, the empirical marginal (histogram) and leading autocorrelations are captured simultaneously. Practical TES modeling is computationally intensive and is effectively carried out with software support. A computerized modeling environment, called TEStool, is briefly reviewed. TEStool supports a heuristic search approach for fitting a TES model to empirical time series. Finally, we exemplify our approach by two examples of TES video source models, constructed from empirical codec bitrate measurements: one at the frame level and the other at the group-of-block level. The examples demonstrate the efficacy of the TES modeling methodology and the TEStool modeling environment.