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Network level perspective in web sessions troubleshooting

机译:Web Sessions故障排除中的网络级透视图

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In the last years, the quantity of data and the number of applications carried over web traffic have been continuously increasing and nowadays web browsing accounts for most of the Internet traffic. In such a scenario, a poor browsing experience can result very annoying to the end user, and the effective identification of the root cause of such bad performance is of primary interest to both the users and the network operators. In this paper, we present a unified framework, based on a novel lightweight open-source publicly available probe and on an original statistical diagnosis algorithm, to correctly and effectively point out the segment of a web connection (eg, local client, backbone network, and DNS server) responsible for a poor web browsing experience. The extensive experimental evaluation carried out in the paper demonstrates the effectiveness of the proposed approach to diagnose poor quality of experience at a large scale.
机译:在过去的几年中,数据数量和通过Web流量携带的应用程序数量不断增加,而今的Web浏览帐户对于大多数互联网流量。在这样的场景中,较差的浏览体验可能导致到最终用户非常烦人,并且有效地识别这种不良性能的根本原因对用户和网络运营商的主要兴趣是主要的兴趣。在本文中,我们介绍了一个统一的框架,基于新颖的轻量级开源公开探测和原始统计诊断算法,正确有效地指出Web连接的段(例如,本地客户端,骨干网,和DNS服务器)负责较差的网络浏览体验。本文中进行的广泛实验评估表明了提出的方法诊断较差的经验质量较差的方法的有效性。

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