A novel view of the dri method for heavy traic limits of eueing systems

Daniela Hurtado-Lange; Siva Theja Maguluri

doi:10.1145/3305218.3305248

A novel view of the dri method for heavy traic limits of eueing systems

Daniela Hurtado-Lange, Siva Theja Maguluri

Managerial Economics, Decision Sciences and Operations

Research output: Contribution to journal › Conference article › peer-review

1 Scopus citations

Abstract

The drift method has been recently developed to study queueing systems in heavy trac [3]. This method was successfully used to obtain the heavy trac scaled sum queue lengths of several systems, even when the so-called complete resource pooling condition is not satised. In this poster, we present a novel view of the drift method to explain why this method works. We believe that this view can be exploited to obtain the joint distribution of the steady-state heavy-trac scaled queue lengths.

Original language	English (US)
Pages (from-to)	81-82
Number of pages	2
Journal	Performance Evaluation Review
Volume	46
Issue number	2
DOIs	https://doi.org/10.1145/3305218.3305248
State	Published - Jan 17 2019
Event	2018 Workshop on MAthematical Performance Modeling and Analysis, MAMA 2018 and Workshop on Critical Infrastructure Network Security, CINS 2018 - Irvine, United States Duration: Jun 1 2018 → …

ASJC Scopus subject areas

Software
Hardware and Architecture
Computer Networks and Communications

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abstract = "The drift method has been recently developed to study queueing systems in heavy trac [3]. This method was successfully used to obtain the heavy trac scaled sum queue lengths of several systems, even when the so-called complete resource pooling condition is not satised. In this poster, we present a novel view of the drift method to explain why this method works. We believe that this view can be exploited to obtain the joint distribution of the steady-state heavy-trac scaled queue lengths.",

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N2 - The drift method has been recently developed to study queueing systems in heavy trac [3]. This method was successfully used to obtain the heavy trac scaled sum queue lengths of several systems, even when the so-called complete resource pooling condition is not satised. In this poster, we present a novel view of the drift method to explain why this method works. We believe that this view can be exploited to obtain the joint distribution of the steady-state heavy-trac scaled queue lengths.

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A novel view of the dri method for heavy traic limits of eueing systems

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