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Modeling of H.264 High Definition Video Traffic Using Discrete-Time Semi-Markov Processes

机译:使用离散时间半马尔可夫过程对H.264高清视频流量进行建模

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Semi-Markov processes (SMPs) are widely used to model various types of data traffic in communication networks. Also, efficient and reliable analysis techniques are available. In this paper, we consider several present methods of deriving the parameters of a discrete-time semi-Markov process from given H.264 video traces in order to model the original traffic adequately. We take the distribution of frame sizes and the autocorrelation of both the original trace and the resulting SMP model into account as key quality indicators. We propose a new evolutionary optimization approach using genetic programming, which is able to significantly improve the accuracy of semi-Markov models of video traces and, at the same time, requires a smaller number of states.
机译:半马尔可夫过程(SMP)被广泛用于对通信网络中各种类型的数据流量进行建模。同样,可以使用有效且可靠的分析技术。在本文中,我们考虑从给定的H.264视频轨迹中导出离散时间半马尔可夫过程的参数的几种当前方法,以便对原始流量进行适当的建模。我们将帧大小的分布以及原始迹线和生成的SMP模型的自相关作为关键质量指标。我们提出了一种使用遗传规划的新的进化优化方法,该方法能够显着提高视频轨迹的半马尔可夫模型的准确性,同时需要更少的状态。

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