Is network traffic approximated by stable Levy motion or fractional Brownian motion?

  • T Mikosch*
  • , S Resnick
  • , H Rootzen
  • , A Stegeman
  • *Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

225 Citations (Scopus)
291 Downloads (Pure)

Abstract

Cumulative broadband network traffic is often thought to be well modeled by fractional Brownian motion (FBM). However, some traffic measurements do not show an agreement with the Gaussian marginal distribution assumption. We show that if connection rates are modest relative to heavy tailed connection length distribution tails, then stable Levy motion is a sensible approximation to cumulative traffic over a time period. If connection rates are large relative to heavy tailed connection length distribution tails, then FBM is the appropriate approximation. The results are framed as limit theorems for a sequence of cumulative input processes whose connection rates are varying in such a way as to remove or induce long range dependence.

Original languageEnglish
Pages (from-to)23-68
Number of pages46
JournalAnnals of applied probability
Volume12
Issue number1
DOIs
Publication statusPublished - Feb-2002

Keywords

  • heavy tails
  • regular variation
  • Pareto tails
  • self-similarity
  • scaling
  • infinite variance
  • stable Levy motion
  • fractional Brownian motion
  • Gaussian approximation
  • ON/OFF process
  • workload process
  • cumulative input process
  • input rate
  • large deviations
  • LONG-RANGE DEPENDENCE
  • HEAVY TAILS
  • MODELS
  • PERFORMANCE
  • QUEUE

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