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YouTube Can Do Better: Getting the Most Out of Video Adaptation

机译：YouTube可以做得更好：充分利用视频改编

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摘要

YouTube, as one of the major HTTP Adaptive Streaming video services, accounts for a large fraction of today's Internet traffic. Therefore, it is important to understand how efficiently YouTube uses available network resources. Previous work observed that the YouTube player replaces previously buffered segments with higher quality segments. This is good for the user as it increases the average quality level. However, the lower quality level segments are discarded and their traffic is redundant and therefore wasted. In this paper, we use two independent approaches to evaluate the efficiency of YouTube's quality adaptation algorithm. The first approach performs regression based on previously collected video views from a large experimental data set. In the second approach we formulate a mixed integer linear program and calculate the optimal video quality adaptation. The results show that the simplistic regression approach gives an accurate estimation of the optimal adaptation. Furthermore, the optimization shows that the Quality of Experience (QoE) can be significantly improved compared to the actual average quality level observed in the real-world experiments, demanding for better video quality adaptation mechanisms by YouTube.
机译：YouTube作为主要的HTTP自适应流视频服务之一，在当今的互联网流量中占很大一部分。因此，重要的是要了解YouTube如何有效利用可用的网络资源。以前的工作表明，YouTube播放器将以前缓冲的片段替换为更高质量的片段。这对用户有利，因为它提高了平均质量水平。但是，较低质量级别的段将被丢弃，并且它们的流量是多余的，因此被浪费了。在本文中，我们使用两种独立的方法来评估YouTube的质量自适应算法的效率。第一种方法基于先前从大型实验数据集中收集的视频观看次数执行回归。在第二种方法中，我们制定了一个混合整数线性程序，并计算了最佳的视频质量适应性。结果表明，简单回归方法可以准确估计最佳适应性。此外，优化结果表明，与真实实验中观察到的实际平均质量水平相比，体验质量（QoE）可以得到显着改善，因此YouTube需要更好的视频质量适应机制。

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