Title

A Comparison of Methods for Estimating the Tail Index of Heavy-tailed Internet Traffic

Comments

© 2007 Springer . Metadata only available on this website. This was a book chapter published in Sobh, T., Elleithy, K., Mahamood, A. and Karim, M. (Eds.), Innovative Algorithms and Techniques in Automation, Industrial Electronics and Telecommunications by Springer in 2007. The original publication is available at http://www.springerlink.com

Abstract

Many researchers have discussed the effects of heavy-tailedness in network traffic patterns and shown that Internet traffic flows exhibit characteristics of self-similarity that can be explained by the heavy-tailedness of the various distributions involved. Self-similarity and heavy-tailedness are of great importance for network capacity planning purposes in which researchers are interested in developing analytical methods for analysing traffic characteristics. Designers of computing and telecommunication systems are increasingly interested in employing heavy-tailed distributions to generate workloads for use in simulation although simulations employing such workloads may show unusual characteristics. In this paper, we describe some of the most useful mechanisms for estimating the tail index, particularly for distributions having the power law observed in different contexts in the Internet.

Disciplines

Computer and Systems Architecture | Digital Communications and Networking | Hardware Systems | Systems and Communications

Recommended Citation

Rezaul, K. M. and Grout, V. (2007). ‘A Comparison of Methods for Estimating the Tail Index of Heavy-tailed Internet Traffic’ in Sobh, T., Elleithy, K., Mahamood, A. and Karim, M. (Eds.), Innovative Algorithms and Techniques in Automation, Industrial Electronics and Telecommunications. Netherlands: Springer. pp.219-222


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