Webprofiler: cooperative diagnosis of web failures

  • Authors:
  • Sharad Agarwal;Nokitas Liogkas;Prashanth Mohan;Venkara N. Padmanabhan

  • Affiliations:
  • MSR Redmond;Knight Capital;UC Berkeley;MSR India

  • Venue:
  • COMSNETS'10 Proceedings of the 2nd international conference on COMmunication systems and NETworks
  • Year:
  • 2010

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Abstract

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.