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Post-Streaming Rate Analysis—A New Approach to Mobile Video Streaming with Predictable Performance

机译:后流速率分析—具有可预测性能的移动视频流的新方法

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Fueled by the growth of 3G/4G mobile networks, mobile video streaming has become one of the main applications in the mobile Internet. Due to mobile networks' inherent bandwidth fluctuations, the industry as well as researchers have developed many adaptive streaming algorithms to compensate for such fluctuations to improve streaming performance. Given the wide range of network settings, it is not surprising that existing algorithms can and do perform differently across different network and system conditions. This work breaks away from the conventional one-size-fits-all approach to designing adaptive streaming systems by developing a new framework called PSRA where past throughput trace data - captured as a by-product of streaming, are analyzed to construct a statistical model to automatically tune the adaptation algorithm for future streaming sessions according to the underlying network and system configurations. Compared to existing approaches, the PSRA-optimized streaming algorithm can achieve predictable, consistent, and controllable streaming performance across a wide-range of network and system configurations. Moreover, PSRA offers to service provider a new tool to precisely control the tradeoff between video quality and streaming performance. Results from extensive trace-driven simulations as well as experiments verified PSRA's performance under real-world mobile network and system configurations.
机译:在3G / 4G移动网络的发展推动下,移动视频流已成为移动Internet的主要应用之一。由于移动网络固有的带宽波动,业界和研究人员开发了许多自适应流算法来补偿这种波动,从而提高了流性能。鉴于网络设置的范围很广,因此在不同的网络和系统条件下,现有算法可以而且确实有不同的表现也就不足为奇了。这项工作通过开发称为PSRA的新框架,打破了传统的“一劳永逸”的方法来设计自适应流系统,在该框架中,对过去的吞吐量跟踪数据(作为流的副产品捕获)进行了分析,以构建统计模型,根据基础网络和系统配置自动调整适应算法,以用于将来的流式会话。与现有方法相比,PSRA优化的流算法可以在广泛的网络和系统配置中实现可预测,一致且可控制的流性能。此外,PSRA还为服务提供商提供了一种新工具,可以精确控制视频质量和流传输性能之间的折衷。广泛的跟踪驱动模拟结果和实验结果验证了PSRA在实际移动网络和系统配置下的性能。

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