A bibliographical guide to self-similar traffic and performance modeling for modern high-speed networks

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Abstract
This paper provides a bibliographical guide to researchers and traffic engineers who are interested in self-similar traffic modeling and analysis. It lists some of the most recent network traffic studies and includes surveys and research papers in the areas of data analysis, statistical inference, mathematical modeling, queueing and performance analysis. It also contains references to other areas of applications (e.g., hydrology, economics, geophysics, biology and biophysics) where similar developments have taken place and where numerous results have been obtained that can often be directly applied in the network traffic context. Heavy-tailed distributions, their relation to self-similar modeling, and corresponding estimation techniques are also covered in this guide.

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