We propose methods for selecting the modelling parameters of H.263-quantized video traffic under two different encoding scenarios. For videos encoded with a constant quantization step (unconstrained), we conclude that a two-parameter power relation holds between the exhibited video bit rate and the quantizer value and that the autocorrelation decay rate remains constant for all cases. On the basis of these results, we propose a generic method for estimating the modelling parameters of unconstrained traffic by means of measuring the statistics of the single “raw” video trace. For rate-controlled video (constrained), we propose an approximate method based on the adjustment of the “shape” parameter of the counterpart—with respect to rate—unconstrained video trace. The convergence of the constructed models is assessed via q-q plots and queuing simulations. On the assumption that the popular MPEG-4 encoders like XVID, DIVX usually employ identical H.263 quantization and rate control schemes, it is expected that the results of this paper also hold for the MPEG-4 part 2 family. 1. Introduction With the rapid spread of multimedia applications and the great progress of video streaming technologies such as the MPEG-4 and H.26x standards, network-based multimedia applications, for example, IPTV, VoD, and videoconference, have become increasingly popular services. Video traffic, which is going to be streamed by these services, is expected to account for large portions of the multimedia traffic in future heterogeneous networks (wireline, wireless, and satellite). Despite the high data rates of the contemporary network settings, there is still a need for quality assurance for the above services especially when a real-time session has to be established (e.g., videoconference or video streaming without buffering options, e-collaboration, remote control, etc.). Since such services rely on the exchange of bandwidth demanding video information, with the MPEG-4 and H.263 encoders being the most commonly used standards for the moment, extensive deployment of these services calls for careful modelling of the associated network traffic, so that the appropriate amount of resources may be anticipated by the network. The video traffic models for these networks must cover a wide range of traffic types and characteristics because the type of the terminals will range from a single home or mobile user (low video bit rate), where rate-constrained (or rate-controlled) video traffic is mainly produced, to a terminal connected to a backbone network (high video bit rate), where the
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