WebProfiler:网络故障的协同诊断

S. Agarwal, Nikitas Liogkas, Prashanth Mohan, V. Padmanabhan
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引用次数: 17

摘要

尽管Web的重要性和覆盖范围有了巨大的增长,但当Web页面加载失败时,用户几乎没有追索权。Web浏览器对此类故障提供的反馈很少,通常只提供重新检查URL或计算机网络设置等一般性建议。因此,用户常常无法诊断Web访问问题,只能随意修改设置,或者稍后再试。我们提倡基于客户端的协作方法来诊断Web浏览失败。我们的系统WebProfiler利用终端主机合作,从多个有利位置对Web访问的成功或失败进行汇总观察。这些信息被输入到一个简单的协作归因算法中。我们在受控测试平台上的评估表明,WebProfiler可以准确地诊断出比单个客户端多3.6倍的故障。我们提出了一个企业网络的WebProfiler的设计和原型实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
WebProfiler: Cooperative diagnosis of Web failures
Despite tremendous growth in the importance and reach of the Web, users have little recourse when a Web page fails to load. Web browsers provide little feedback on such failures, typically offering only generic suggestions such as re-checking the URL or the machine's network settings. Hence, users are often unable to diagnose Web access problems, and resort to haphazardly modifying their settings or simply trying again later. We advocate a client-based collaborative approach for diagnosing Web browsing failures. Our system, WebProfiler, leverages end-host cooperation to pool together observations on the success or failure of Web accesses from multiple vantage points. These are fed into a simple, collaborative blame attribution algorithm. Our evaluation on a controlled testbed shows WebProfiler can accurately diagnose 3.6 times as many failures than possible from a single client's perspective. We present the design and prototype implementation of WebProfiler for an enterprise network.
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