YouTube everywhere: impact of device and infrastructure synergies on user experience
YouTube everywhere: impact of device and infrastructure synergies on user experience
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DOI：
10.1145/2068816.2068849
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发表时间：
2011-11
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影响因子：
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通讯作者：
A. Finamore;M. Mellia;M. Munafò;R. Torres;Sanjay G. Rao
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作者：
A. Finamore;M. Mellia;M. Munafò;R. Torres;Sanjay G. Rao
在本文中，我们提出了一项完整的测量研究，将移动设备（智能手机、平板电脑）产生的 YouTube 流量与普通 PC（台式机、笔记本电脑、上网本）产生的流量进行比较。我们调查用户的行为并将其与系统性能相关联。我们的测量是使用独特的数据集进行的，这些数据集是从欧洲和美国两个国家的全国互联网服务提供商和大学校园的有利位置收集的。我们的结果表明，在各种用户位置、访问技术和用户设备上，用户访问模式都是相似的。用户坚持使用默认的播放器配置，例如，不更改视频分辨率或很少启用全屏播放。此外，用户中止视频播放的情况也很常见，60% 的视频观看时间不超过其持续时间的 20%。我们表明 YouTube 系统针对 PC 访问进行了高度优化，并利用积极的缓冲策略来保证出色的视频播放。然而，这会导致 25%-39% 的数据被不必要地传输，因为用户很早就中止了播放。当考虑到移动设备时，这种传输数据的浪费甚至更高。这些设备提供的有限存储空间使得视频下载更加复杂且整体效率较低，因此客户端下载的数据通常比实际视频大小多。总体而言，这一结果需要针对 PC 和移动访问进行更好的系统优化。
In this paper we present a complete measurement study that compares YouTube traffic generated by mobile devices (smart-phones,tablets) with traffic generated by common PCs (desktops, notebooks, netbooks). We investigate the users' behavior and correlate it with the system performance. Our measurements are performed using unique data sets which are collected from vantage points in nation-wide ISPs and University campuses from two countries in Europe and the U.S. Our results show that the user access patterns are similar across a wide range of user locations, access technologies and user devices. Users stick with default player configurations, e.g., not changing video resolution or rarely enabling full screen playback. Furthermore it is very common that users abort video playback, with 60% of videos watched for no more than 20% of their duration. We show that the YouTube system is highly optimized for PC access and leverages aggressive buffering policies to guarantee excellent video playback. This however causes 25%-39% of data to be unnecessarily transferred, since users abort the playback very early. This waste of data transferred is even higher when mobile devices are considered. The limited storage offered by those devices makes the video download more complicated and overall less efficient, so that clients typically download more data than the actual video size. Overall, this result calls for better system optimization for both, PC and mobile accesses.