Simulation run length planning for stochastic loss models

We derive approximate formulas for the asymptotic variance of estimators of the steady-state blocking probability in a multi-server loss system. These formulas can be used to predict simulation run lengths required to obtain desired statistical precision before the simulation has been run, which can...

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Bibliographic Details
Published in:Proceedings of the 27th conference on Winter simulation pp. 1384 - 1391
Main Authors: Srikant, Rayadurgam, Whitt, Ward
Format: Conference Proceeding
Language:English
Published: Washington, DC, USA IEEE Computer Society 01.12.1995
Series:ACM Conferences
Subjects:
Applied computing > Computers in other domains > Personal computers and PC applications > Computer games
Computing methodologies > Machine learning
Computing methodologies > Modeling and simulation
Information systems > Information systems applications > Multimedia information systems > Massively multiplayer online games
Mathematics of computing > Mathematical analysis > Functional analysis > Approximation
Mathematics of computing > Mathematical analysis > Numerical analysis
Mathematics of computing > Probability and statistics
Software and its engineering > Software organization and properties > Contextual software domains > Virtual worlds software > Interactive games
Theory of computation > Design and analysis of algorithms > Approximation algorithms analysis
Theory of computation > Theory and algorithms for application domains > Algorithmic game theory and mechanism design
ISBN:0780330188, 9780780330184
Online Access:Get full text
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Summary:We derive approximate formulas for the asymptotic variance of estimators of the steady-state blocking probability in a multi-server loss system. These formulas can be used to predict simulation run lengths required to obtain desired statistical precision before the simulation has been run, which can aid in the design of simulation experiments. It is natural to delete an initial portion of the simulation run to allow the system to approach steady state when it starts out empty. As the system size increases, the time to approach steady state becomes a greater portion of the overall simulation time as system size increases.
Bibliography:SourceType-Conference Papers & Proceedings-1
ObjectType-Conference Paper-1
content type line 25
ISBN:0780330188
9780780330184
DOI:10.1145/224401.224824