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A NOVEL COST-DISTORTION OPTIMIZATION FRAMEWORK FOR VIDEO STREAMING OVER DIFFERENTIATED SERVICES NETWORKS

机译:差异化服务网络上视频流的新型成本失真优化框架

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This paper presents a novel framework for streaming video over a Differentiated Services (DiflServ) network that jointly considers video source coding, packet classification and error concealment within the scope of cost-distortion optimization. Our formulation incorporates the random network delay for each packet into the calculation of the probability of packet loss and manages the end-to-end packet delay by selecting the encoding parameters and packet priority. We formulate two approaches to evaluate the performance of the proposed framework: a minimum distortion approach and a minimum cost approach, in which the encoding mode and priority class for each packet are optimally selected so as to minimize the total distortion subject to cost constraints, or to minimize the total cost subject to end-to-end distortion constraints. Simulation results demonstrate the advantage of jointly adapting the source coding and packet classification.
机译:本文介绍了一种新颖的框架,用于通过差分服务(DIFLSERV)网络流传输视频,该网络在成本失真优化范围内共同考虑视频源编码,分组分类和错误隐藏。我们的配方包括每个分组的随机网络延迟,通过选择编码参数和分组优先级来管理分组丢失的概率并管理端到端分组延迟。我们制定了两种方法来评估所提出的框架的性能:最小失真方法和最小成本方法,其中每个分组的编码模式和优先级的最佳选择,以便最大限度地减少经过成本约束的总失真,或者最大限度地减少对端到端失真约束的总成本。仿真结果证明了共同调整源编码和分组分类的优点。

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