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

• 成果类型: Article
• 署名作者: Mikosch, T; Resnick, S; Rootzén, H; Stegeman, A
• 署名单位: University of Copenhagen; Cornell University; Chalmers University of Technology; University of Groningen
• 刊物名称: ANNALS OF APPLIED PROBABILITY
• ISSN/ISSBN: 1050-5164
• 发表日期: 2002
• 页码: 23-68
• 关键词: long-range dependence; heavy; performance; models; QUEUE

摘要

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.