A discrete event simulation model for evaluating the performances of an m/g/c/c state dependent queuing system
M/G/C/C state dependent queuing networks consider service rates as a function of the number of residing entities (e.g., pedestrians, vehicles, and products). However, modeling such dynamic rates is not supported in modern Discrete Simulation System (DES) software. We designed an approach to cater th...
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| Veröffentlicht in: | PloS one 2013-04, Vol.8 (4), p.e58402-e58402 |
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| creator | Khalid, Ruzelan Nawawi, Mohd Kamal M Kawsar, Luthful A Ghani, Noraida A Kamil, Anton A Mustafa, Adli |
| description | M/G/C/C state dependent queuing networks consider service rates as a function of the number of residing entities (e.g., pedestrians, vehicles, and products). However, modeling such dynamic rates is not supported in modern Discrete Simulation System (DES) software. We designed an approach to cater this limitation and used it to construct the M/G/C/C state-dependent queuing model in Arena software. Using the model, we have evaluated and analyzed the impacts of various arrival rates to the throughput, the blocking probability, the expected service time and the expected number of entities in a complex network topology. Results indicated that there is a range of arrival rates for each network where the simulation results fluctuate drastically across replications and this causes the simulation results and analytical results exhibit discrepancies. Detail results that show how tally the simulation results and the analytical results in both abstract and graphical forms and some scientific justifications for these have been documented and discussed. |
| doi_str_mv | 10.1371/journal.pone.0058402 |
| format | Article |
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However, modeling such dynamic rates is not supported in modern Discrete Simulation System (DES) software. We designed an approach to cater this limitation and used it to construct the M/G/C/C state-dependent queuing model in Arena software. Using the model, we have evaluated and analyzed the impacts of various arrival rates to the throughput, the blocking probability, the expected service time and the expected number of entities in a complex network topology. Results indicated that there is a range of arrival rates for each network where the simulation results fluctuate drastically across replications and this causes the simulation results and analytical results exhibit discrepancies. Detail results that show how tally the simulation results and the analytical results in both abstract and graphical forms and some scientific justifications for these have been documented and discussed.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0058402</identifier><identifier>PMID: 23560037</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Analysis ; C plus plus ; Computer programs ; Computer Science ; Computer Simulation ; Discrete event systems ; Distance learning ; Education ; Efficiency, Organizational - statistics & numerical data ; Humans ; Markov Chains ; Mathematics ; Models, Statistical ; Operations research ; Pedestrians ; Probability ; Queues ; Queuing theory ; Simulation ; Social and Behavioral Sciences ; Software ; Topology</subject><ispartof>PloS one, 2013-04, Vol.8 (4), p.e58402-e58402</ispartof><rights>COPYRIGHT 2013 Public Library of Science</rights><rights>2013 Khalid et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: https://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. 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However, modeling such dynamic rates is not supported in modern Discrete Simulation System (DES) software. We designed an approach to cater this limitation and used it to construct the M/G/C/C state-dependent queuing model in Arena software. Using the model, we have evaluated and analyzed the impacts of various arrival rates to the throughput, the blocking probability, the expected service time and the expected number of entities in a complex network topology. Results indicated that there is a range of arrival rates for each network where the simulation results fluctuate drastically across replications and this causes the simulation results and analytical results exhibit discrepancies. 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| subjects | Analysis C plus plus Computer programs Computer Science Computer Simulation Discrete event systems Distance learning Education Efficiency, Organizational - statistics & numerical data Humans Markov Chains Mathematics Models, Statistical Operations research Pedestrians Probability Queues Queuing theory Simulation Social and Behavioral Sciences Software Topology |
| title | A discrete event simulation model for evaluating the performances of an m/g/c/c state dependent queuing system |
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