基于qos的YouTube流量性能下降分析

P. Casas, A. D'Alconzo, P. Fiadino, A. Bär, A. Finamore
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引用次数: 13

摘要

YouTube是当今互联网上最受欢迎的服务。谷歌依靠其庞大的内容分发网络(CDN),通过使用动态服务器选择策略,将YouTube视频尽可能地推向终端用户,以提高他们的体验质量(QoE)。这种流量传递策略可能对通过提供访问的互联网服务提供商(isp)路由的流量产生相关影响,但最重要的是,它们可能对最终用户QoE产生负面影响。在本文中,我们阐明了在YouTube流量中诊断基于qos的性能下降事件的问题。通过分析一个月来在欧洲大型互联网服务提供商的网络上收集的YouTube流量痕迹,我们特别确定并深入研究了谷歌的CDN服务器选择政策,该政策在高峰加载时间的几天内对YouTube用户的观看体验产生了负面影响。该分析结合了端到端YouTube交付服务的用户端视角和CDN视角来诊断问题。本文的主要贡献有三个方面:首先,我们根据Google CDN服务器的流量特征和配置行为对YouTube服务进行了大规模的表征。其次,我们引入了简单而有效的基于qos的kpi,从最终用户的角度监控YouTube视频。最后也是最重要的是,我们分析并提供了由CDN服务器选择策略引起的基于qos的YouTube异常发生的证据,这些异常通常在某种程度上隐藏在最终用户的常识之外。对于互联网服务提供商来说,这是一个主要问题,即使谷歌是罪魁祸首,当此类事件发生时,他们的声誉也会下降。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On the analysis of QoE-based performance degradation in YouTube traffic
YouTube is the most popular service in today's Internet. Google relies on its massive Content Delivery Network (CDN) to push YouTube videos as close as possible to the end-users to improve their Quality of Experience (QoE), using dynamic server selection strategies. Such traffic delivery policies can have a relevant impact on the traffic routed through the Internet Service Providers (ISPs) providing the access, but most importantly, they can have negative effects on the end-user QoE. In this paper we shed light on the problem of diagnosing QoE-based performance degradation events in YouTube's traffic. Through the analysis of one month of YouTube flow traces collected at the network of a large European ISP, we particularly identify and drill down a Google's CDN server selection policy negatively impacting the watching experience of YouTube users during several days at peak-load times. The analysis combines both the user-side perspective and the CDN perspective of the end-to-end YouTube delivery service to diagnose the problem. The main contributions of the paper are threefold: firstly, we provide a large-scale characterization of the YouTube service in terms of traffic characteristics and provisioning behavior of the Google CDN servers. Secondly, we introduce simple yet effective QoE-based KPIs to monitor YouTube videos from the end-user perspective. Finally and most important, we analyze and provide evidence of the occurrence of QoE-based YouTube anomalies induced by CDN server selection policies, which are somehow normally hidden from the common knowledge of the end-user. This is a main issue for ISPs, who see their reputation degrade when such events occur, even if Google is the culprit.
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