document: On the lack of typical behavior in the global Web traffic network We offer the first large-scale analysis of Web traffic based on network flow data . Using data collected on the Internet2 network , we constructed a weighted bipartite client-server host graph containing more than 18 x 106 vertices and 68 x 106 edges valued by relative traffic flows . When considered as a traffic map of the World-Wide Web , the generated graph provides valuable information on the statistical patterns that characterize the global information flow on the Web . Statistical analysis shows that client-server connections and traffic flows exhibit heavy-tailed probability distributions lacking any typical scale . In particular , the absence of an intrinsic average in some of the distributions implies the absence of a prototypical scale appropriate for server design , Web-centric network design , or traffic modeling . The inspection of the amount of traffic handled by clients and servers and their number of connections highlights non-trivial correlations between information flow and patterns of connectivity as well as the presence of anomalous statistical patterns related to the behavior of users on the Web . The results presented here may impact considerably the modeling , scalability analysis , and behavioral study of Web applications .
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