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The Fundamentals of Heavy-tails: Properties, Emergence, and Identification

Nair, Jayakrishnan and Wierman, Adam and Zwart, Bert (2013) The Fundamentals of Heavy-tails: Properties, Emergence, and Identification. In: SIGMETRICS '13 Proceedings of the ACM SIGMETRICS/international conference on Measurement and modeling of computer systems. ACM , New York, NY, pp. 387-388. ISBN 978-1-4503-1900-3.

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Heavy-tails are a continual source of excitement and confusion across disciplines as they are repeatedly "discovered" in new contexts. This is especially true within computer systems, where heavy-tails seemingly pop up everywhere -- from degree distributions in the internet and social networks to file sizes and interarrival times of workloads. However, despite nearly a decade of work on heavy-tails they are still treated as mysterious, surprising, and even controversial. The goal of this tutorial is to show that heavy-tailed distributions need not be mysterious and should not be surprising or controversial. In particular, we will demystify heavy-tailed distributions by showing how to reason formally about their counter-intuitive properties; we will highlight that their emergence should be expected (not surprising) by showing that a wide variety of general processes lead to heavy-tailed distributions; and we will highlight that most of the controversy surrounding heavy-tails is the result of bad statistics, and can be avoided by using the proper tools.

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Subject Keywords:G.3 [Mathematics of computing]: Probability and Statistics; Heavy-tailed distributions
Record Number:CaltechAUTHORS:20130828-104051418
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:40974
Deposited On:29 Aug 2013 23:49
Last Modified:10 Nov 2021 04:24

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