A most probable path approach to queueing systems with general Gaussian input

Petteri Mannersalo, Ilkka Norros

Research output: Contribution to journalArticleScientificpeer-review

61 Citations (Scopus)

Abstract

This paper develops a rather general and easy-to-use methodology how to obtain good approximations for queue length distributions in priority and generalized processor sharing systems where the cumulative input traffic streams are modeled as general Gaussian processes with stationary increments. The idea is to identify the most probable path in the threshold-exceeding event, or a heuristic approximation of it, and then to use probability estimates based on this path. The method is particularly useful for long-range dependent traffic and complicated traffic mixes, which are difficult to handle with traditional queueing theory.
Original languageEnglish
Pages (from-to)399-412
JournalComputer Networks
Volume40
Issue number3
DOIs
Publication statusPublished - 2002
MoE publication typeA1 Journal article-refereed

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Queueing theory

Keywords

  • gaussian processes
  • generalized processor sharing
  • priority queues
  • most probable paths

Cite this

Mannersalo, Petteri ; Norros, Ilkka. / A most probable path approach to queueing systems with general Gaussian input. In: Computer Networks. 2002 ; Vol. 40, No. 3. pp. 399-412.
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A most probable path approach to queueing systems with general Gaussian input. / Mannersalo, Petteri; Norros, Ilkka.

In: Computer Networks, Vol. 40, No. 3, 2002, p. 399-412.

Research output: Contribution to journalArticleScientificpeer-review

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AU - Norros, Ilkka

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AB - This paper develops a rather general and easy-to-use methodology how to obtain good approximations for queue length distributions in priority and generalized processor sharing systems where the cumulative input traffic streams are modeled as general Gaussian processes with stationary increments. The idea is to identify the most probable path in the threshold-exceeding event, or a heuristic approximation of it, and then to use probability estimates based on this path. The method is particularly useful for long-range dependent traffic and complicated traffic mixes, which are difficult to handle with traditional queueing theory.

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KW - priority queues

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JO - Computer Networks

JF - Computer Networks

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