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How Hard are Steady-State Queueing Simulations?

Authors:

Shane G. HendersonAuthors Info & Claims

ACM Transactions on Modeling and Computer Simulation (TOMACS), Volume 25, Issue 4

Article No.: 27, Pages 1 - 21

https://doi.org/10.1145/2749460

Published: 16 November 2015 Publication History

Abstract

Some queueing systems require tremendously long simulation runlengths to obtain accurate estimators of certain steady-state performance measures when the servers are heavily utilized. However, this is not uniformly the case. We analyze a number of single-station Markovian queueing models, demonstrating that several steady-state performance measures can be accurately estimated with modest runlengths. Our analysis reinforces the meta result that if the queue is “well dimensioned,” then simulation runlengths will be modest. Queueing systems can be well dimensioned because customers abandon if they are forced to wait in line too long, or because the queue is operated in the “quality- and efficiency-driven regime” in which servers are heavily utilized but wait times are short. The results are based on computing or bounding the asymptotic variance and bias for several standard single-station queueing models and performance measures.

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Cited By

Liu WSun X(2022)Energy-Aware and Delay-Sensitive Management of a Drone Delivery SystemManufacturing & Service Operations Management10.1287/msom.2021.105624:3(1294-1310)Online publication date: May-2022
https://doi.org/10.1287/msom.2021.1056
Niño-Mora J(2020)Solving Poisson’s equation for birth-death chains: Structure, instability, and accurate approximationPerformance Evaluation10.1016/j.peva.2020.102163(102163)Online publication date: Oct-2020
https://doi.org/10.1016/j.peva.2020.102163
Sun XWhitt W(2018)Creating Work Breaks from Available IdlenessManufacturing & Service Operations Management10.1287/msom.2017.068220:4(721-736)Online publication date: 1-Oct-2018
https://dl.acm.org/doi/10.1287/msom.2017.0682
Show More Cited By

Index Terms

How Hard are Steady-State Queueing Simulations?
1. Computing methodologies
  1. Modeling and simulation
    1. Simulation evaluation
2. Mathematics of computing
  1. Probability and statistics

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Published In

cover image ACM Transactions on Modeling and Computer Simulation

ACM Transactions on Modeling and Computer Simulation Volume 25, Issue 4

Special Issue on Don Iglehart

November 2015

139 pages

ISSN:1049-3301

EISSN:1558-1195

DOI:10.1145/2774955

Editor:
Adelinde M. Uhrmacher
University of Rostock, Germany

Issue’s Table of Contents

Copyright © 2015 ACM.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 16 November 2015

Accepted: 01 March 2015

Revised: 01 January 2015

Received: 01 July 2013

Published in TOMACS Volume 25, Issue 4

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Cited By

Liu WSun X(2022)Energy-Aware and Delay-Sensitive Management of a Drone Delivery SystemManufacturing & Service Operations Management10.1287/msom.2021.105624:3(1294-1310)Online publication date: May-2022
https://doi.org/10.1287/msom.2021.1056
Niño-Mora J(2020)Solving Poisson’s equation for birth-death chains: Structure, instability, and accurate approximationPerformance Evaluation10.1016/j.peva.2020.102163(102163)Online publication date: Oct-2020
https://doi.org/10.1016/j.peva.2020.102163
Sun XWhitt W(2018)Creating Work Breaks from Available IdlenessManufacturing & Service Operations Management10.1287/msom.2017.068220:4(721-736)Online publication date: 1-Oct-2018
https://dl.acm.org/doi/10.1287/msom.2017.0682
Liu WSun X(undefined)Dynamic Scheduling of a Battery-Operated QueueSSRN Electronic Journal10.2139/ssrn.3542316
https://doi.org/10.2139/ssrn.3542316

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