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首页> 外文会议>2016 IFIP Networking Conference and Workshops >Sacrificing efficiency for quality of experience: YouTube's redundant traffic behavior
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Sacrificing efficiency for quality of experience: YouTube's redundant traffic behavior

机译：牺牲体验质量的效率：YouTube的多余流量行为

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摘要

Internet traffic reports show that YouTube is one of the major sources of data traffic world-wide. Furthermore, the data traffic shifts from mostly fixed landlines to cellular data connections where bandwidth is sparse and expensive. Previous studies revealed that YouTube uses a user-friendly HTTP Adaptive Streaming (HAS) strategy which sacrifices bandwidth efficiency to increase the average playback quality for the user. That way, it happens that the same video segment is transmitted in two or more quality levels, but only one can be shown to the user. We denote this as redundant traffic and this work is dedicated to understanding the influence factors on the amount of redundant traffic. This paper presents the results of a large-scale study with over 12,000 video views over a bottleneck link shaped to various bandwidths. We first evaluate the playback characteristics and show that YouTube's HAS algorithm linearly increases the average playback quality with the available bandwidth while at the same time video buffering is sub-linearly decreased. Furthermore, we identify video-dependent bandwidths which optimize the playback time on a quality level. Afterward, we show that this is achieved by discarding lower layer segments and therefore paid with redundant traffic of up to 40 %. We evaluate the overall efficiency of the system and show that YouTube is able to improve the average quality level by up to 0.7 quality levels by using this adaptation strategy. However, a penalty of 0.5 quality levels is paid for it due to the discarded data of the lower quality segments.
机译：互联网流量报告显示，YouTube是全球范围内数据流量的主要来源之一。此外，数据流量从大部分固定的固定电话转移到带宽稀疏且昂贵的蜂窝数据连接。先前的研究表明，YouTube使用了用户友好的HTTP自适应流（HAS）策略，该策略牺牲了带宽效率来提高用户的平均播放质量。这样，碰巧以两个或两个以上质量等级传输同一视频片段，但是只能向用户显示一个视频片段。我们将其表示为冗余流量，并且这项工作旨在了解冗余流量数量的影响因素。本文介绍了一项大规模研究的结果，该研究在不同带宽的瓶颈链路上观看了12,000多个视频。我们首先评估了播放特性，并表明YouTube的HAS算法在可用带宽的情况下线性提高了平均播放质量，而同时视频缓冲则在亚线性范围内减小。此外，我们确定了视频相关的带宽，这些带宽可以在质量上优化播放时间。此后，我们表明这是通过丢弃较低的层段来实现的，因此可以支付高达40％的冗余流量。我们评估了系统的整体效率，并表明YouTube通过使用这种适应策略可以将平均质量提高多达0.7个质量水平。但是，由于丢弃了较低质量段的数据，因此为此付出了0.5个质量级别的罚款。

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