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...
Uložené v:
| Vydané v: | Proceedings of the 27th conference on Winter simulation s. 1384 - 1391 |
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| Hlavní autori: | , |
| Médium: | Konferenčný príspevok.. |
| Jazyk: | English |
| Vydavateľské údaje: |
Washington, DC, USA
IEEE Computer Society
01.12.1995
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| Edícia: | ACM Conferences |
| Predmet: |
Applied computing
> Computers in other domains
> Personal computers and PC applications
> Computer games
Information systems
> Information systems applications
> Multimedia information systems
> Massively multiplayer online games
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| ISBN: | 0780330188, 9780780330184 |
| On-line prístup: | Získať plný text |
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| Shrnutí: | 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. |
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| Bibliografia: | SourceType-Conference Papers & Proceedings-1 ObjectType-Conference Paper-1 content type line 25 |
| ISBN: | 0780330188 9780780330184 |
| DOI: | 10.1145/224401.224824 |

