Regenerative exact simulation for multiserver job model
Perfect/exact sampling has been used in situations, where the underlying distribution from which random samples are of interest is unknown or complex, for more than three decades now. However, to apply perfect sampling techniques to specific models, additional techniques are required. In this paper,...
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| Veröffentlicht in: | Cluster computing Jg. 28; H. 14; S. 937 |
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| Abstract | Perfect/exact sampling has been used in situations, where the underlying distribution from which random samples are of interest is unknown or complex, for more than three decades now. However, to apply perfect sampling techniques to specific models, additional techniques are required. In this paper, the perfect sampling technique is adapted to study a workload process as well as the per-class waiting times of customers in a computing cluster model (also known as the multiserver job model) by using stochastic comparison to a single-server queue, for the first time. Numerical experiments demonstrate the effectiveness of the method in scenarios when the service times have heavy-tailed (Pareto), phase-type, and exponential distributions. |
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| AbstractList | Perfect/exact sampling has been used in situations, where the underlying distribution from which random samples are of interest is unknown or complex, for more than three decades now. However, to apply perfect sampling techniques to specific models, additional techniques are required. In this paper, the perfect sampling technique is adapted to study a workload process as well as the per-class waiting times of customers in a computing cluster model (also known as the multiserver job model) by using stochastic comparison to a single-server queue, for the first time. Numerical experiments demonstrate the effectiveness of the method in scenarios when the service times have heavy-tailed (Pareto), phase-type, and exponential distributions. |
| ArticleNumber | 937 |
| Author | Rumyantsev, Alexander Golovin, Alexander Chakravarthy, Srinivas |
| Author_xml | – sequence: 1 givenname: Alexander surname: Golovin fullname: Golovin, Alexander organization: SMITS Lab, Institute of Applied Mathematical Research, Karelian Research Center of RAS, Department of Applied Mathematics and Cybernetics, Petrozavodsk State University – sequence: 2 givenname: Alexander surname: Rumyantsev fullname: Rumyantsev, Alexander email: ar0@krc.karelia.ru organization: SMITS Lab, Institute of Applied Mathematical Research, Karelian Research Center of RAS, Department of Applied Mathematics and Cybernetics, Petrozavodsk State University – sequence: 3 givenname: Srinivas surname: Chakravarthy fullname: Chakravarthy, Srinivas organization: Kettering University |
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| Keywords | Workload vector 65C20 Perfect sampling Multiserver job model Stochastic monotonicity Kiefer–Wolfowitz recursion Busy cycle 60K25 |
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| SubjectTerms | Algorithms Computer Communication Networks Computer Science Equilibrium Expected values Operating Systems Processor Architectures Queuing theory Sampling methods Simulation Supercomputers Workloads |
| Title | Regenerative exact simulation for multiserver job model |
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