Extremal Dependence: Internet Traffic Applications

F. Hernandezx-Campos, K. Jeffay, C. Park, S. Marron, and S. Resnick
Stochastic Models
Volume 21, Number 1, 2005, pages 1-35.

ABSTRACT: For bivariate heavy tailed data, the extremes may carry distinctive dependence information not seen from moderate values. For example, a large value in one component may help cause a large value in the other. This is the idea behind the notion of extremal dependence. We discuss ways to detect and measure extremal dependence. We apply the techniques discussed to internet data and conclude that for files transferred, file size and throughput (the inferred rate at which the file is transferred) exhibit extremal independence.

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