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On Modeling MPEG Video at the Frame Level Using Self-Similar Processes

机译:在使用自我类似过程在帧级模拟MPEG视频

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MPEG video traffic is expected to represent most of the load in the future high-speed networks. Adequate traffic models for MPEG Variable Bit-Rate (VBR) video are thus important for network design, performance evaluation, admission control and resource allocation. Many models for VBR video traffic have been proposed in the literature. However, while the GOP-level process has been widely analyzed in literature, and so the inter-GOP correlation, little effort has been devoted up to now to the frame-level processes, and so to the intra-GOP correlations, even though it is a fundamental characteristic of MPEG traffic and it might have an important impact on queueing performance. In this work, we compare different solutions proposed in the literature to obtain MPEG frame-level processes, depending on the performance metric to study (loss rate, mean delay and jitter). Besides, we claim for the use of self-similar processes, and more concretely, Gaussian F-ARIMA(1,d,0) processes, to adequately capture the correlation structures involved in MPEG video.
机译:预计MPEG视频流量将表示未来的高速网络中的大部分负载。因此,MPEG变量比特率(VBR)视频的足够交通模型对于网络设计,性能评估,准入控制和资源分配是重要的。在文献中已经提出了许多VBR视频流量模型。然而,虽然GOP级过程已被广泛分析文献,因此GOP间相关性,但现在已经努力到达帧级过程,即使它的相关相关性,即使它是MPEG交通的基本特征,它可能对排队性能产生重要影响。在这项工作中,我们比较文献中提出的不同解决方案,以获得MPEG帧级过程,这取决于研究的性能度量(损失率,平均延迟和抖动)。此外,我们要求使用自类似过程,更具体地,高斯F-ARIMA(1,D,0)的过程,以充分捕获MPEG视频中涉及的相关结构。

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