Abstract
If data traffic were Poisson, increases in the amount of traffic
aggregated on a network would rapidly decrease the relative size of
bursts. The discovery of pervasive long-range dependence demonstrates
that real network traffic is burstier than any possible Poisson model.
We present evidence that, despite being non-Poisson, aggregating Web
traffic causes it to smooth out as rapidly as Poisson traffic. That is,
the relationship between changes in mean bandwidth and changes in
variance is the same for Web traffic as it is for Poisson traffic. We
derive our evidence from traces of real traffic in two ways: first, by
observing how variance changes over the large range of mean bandwidths
present in 24-hour traces; second, by observing the relationship of
variance and mean bandwidth for individual users and combinations of
users. Our conclusion, that variance changes linearly with mean
bandwidth, should be useful (and encouraging) to anyone provisioning a
network for a large aggregate load of Web traffic
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