移动视频流中的数据浪费

Guanghui Zhang, Jack Y. B. Lee
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引用次数: 4

摘要

移动视频流现在在移动用户中无处不在。这项工作调查了一个经常被忽视的问题-由于用户提前离开而无法播放下载的视频数据的数据浪费。经验测量表明,数据浪费非常严重,例如,大约20%的下载数据实际上被浪费了。此外,不仅当前的商业流媒体平台存在大量数据浪费,文献中提出的高级自适应流媒体算法也存在大量数据浪费。这项工作开发了一个新的流后浪费分析(PSWA)框架,通过将现有的自适应流算法转换为浪费感知来解决问题。PSWA使服务提供商能够控制数据浪费和流体验质量(QoE)之间的权衡。最值得注意的是,PSWA可以实现显著的数据浪费减少(例如,超过70%),即使不会对QoE产生负面影响。PSWA可以应用于现有或未来的自适应流媒体算法,从而为当前和未来的流媒体服务中的数据浪费提供了一个实用的解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On data wastage in mobile video streaming
Mobile video streaming is now ubiquitous among mobile users. This work investigated an often-neglected problem — data wastage where downloaded video data were not played back due to user early departure. Empirical measurements showed that data wastage is significant, e.g., around 20% of data downloaded were in fact wasted. Moreover, substantial data wastage exists not only in current commercial streaming platforms, but also in advanced adaptive streaming algorithms proposed in the literature. This work developed a new Post-Streaming Wastage Analysis (PSWA) framework to tackle the problem by converting existing adaptive streaming algorithms into wastage-aware. PSWA enables the service provider to control the tradeoff between data wastage and streaming quality-of-experience (QoE). Most remarkably, PSWA can achieve significant data wastage reduction (e.g., over 70%) even without negatively impacting QoE. PSWA can be applied to existing or future adaptive streaming algorithms and thus offers a practical solution to data wastage in current and future streaming services.
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