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Rate-distortion optimized streaming of packetized media

机译:率失真优化的打包媒体流

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This paper addresses the problem of streaming packetized media over a lossy packet network in a rate-distortion optimized way. We show that although the data units in a media presentation generally depend on each other according to a directed acyclic graph, the problem of rate-distortion optimized streaming of an entire presentation can be reduced to the problem of error-cost optimized transmission of an isolated data unit. We show how to solve the latter problem in a variety of scenarios, including the important common scenario of sender-driven streaming with feedback over a best-effort network, which we couch in the framework of Markov decision processes. We derive a fast practical algorithm for nearly optimal streaming in this scenario, and we derive a general purpose iterative descent algorithm for locally optimal streaming in arbitrary scenarios. Experimental results show that systems based on our algorithms have steady-state gains of 2-6 dB or more over systems that are not rate-distortion optimized. Furthermore, our systems essentially achieve the best possible performance: the operational distortion-rate function of the source at the capacity of the packet erasure channel.
机译:本文以速率失真优化的方式解决了有损分组网络上流式打包媒体的问题。我们表明,尽管媒体演示文稿中的数据单元通常根据有向无环图相互依赖,但是整个演示文稿的速率失真优化流问题可以减少到错误成本优化的独立传输问题。数据单元。我们展示了如何在各种情况下解决后一个问题,包括重要的发送方驱动的常见情况以及通过尽力而为网络提供反馈的情况,我们将其解决在马尔可夫决策过程的框架中。我们推导了一种在这种情况下用于几乎最佳流的快速实用算法,并且我们推导了在任意情况下用于局部最优流的通用迭代下降算法。实验结果表明,与未经速率失真优化的系统相比,基于我们算法的系统具有2-6 dB或更高的稳态增益。此外,我们的系统实质上达到了最佳性能:在分组擦除通道的容量下,源的操作失真率功能。

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