Web traffic modeling exploiting TCP connections' temporal clustering through HTML-REDUCE

This article presents a measurement analysis methodology that, starting fro m packet-level traces, identifies some statistics useful to characterize We b traffic, such as page size, page request frequency, and the user's think time between the download of pages. The methodology was implemented in a to ol named HTML-REDUCE and applied on traces collected in CSELT's corporate n etwork. For each identified statistic the analytic expression best approxim ating its empirical distribution is searched. A simplified model for bandwi dth dimensioning in the server-to-client direction is then presented and va lidated through comparison with full protocol stack simulations. The model only requires the page request frequency of an aggregate of clients and the first two moments of page size distribution.