Approximate Distributed K-Means Clustering over a Peer-to-Peer Network
IEEE Transactions on Knowledge and Data Engineering
Netalyzr: illuminating the edge network
IMC '10 Proceedings of the 10th ACM SIGCOMM conference on Internet measurement
HostView: annotating end-host performance measurements with user feedback
ACM SIGMETRICS Performance Evaluation Review
Trouble shooting interactive web sessions in a home environment
Proceedings of the 2nd ACM SIGCOMM workshop on Home networks
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Web browsing is a very common way of using the Internet to, among others, read news, do on-line shopping, or search for user generated content such as YouTube or Dailymotion. Traditional evaluations of web surfing focus on objectively measured Quality of Service (QoS) metrics such as loss rate or round-trip times; In this paper, we propose to use K-means clustering to share knowledge about the performance of the same web page experienced by different clients. Such technique allows to discover and explain the performance differences among users and identify the root causes for poor performances.