Transient Model for Jackson Networks and Its Approximation

Mohamed, Ahmed M.; Lipsky, Lester; Ammar, Reda A.

doi:10.1007/978-3-540-27860-3_19

Cited by 3 publications

(4 citation statements)

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“…In a previous work, we developed a transient model for Jackson networks for exponential distributions [23]. In this paper we introduce a transient model to study the transient behavior of Jackson networks for other distributions (e.g., Erlangian and Hyperexponential).…”

Section: Introductionmentioning

confidence: 99%

“…However, there is a computational problem in attempting to use this model for large systems. An approximation to the transient model using the steady-state solution was presented to overcome such problems [21].…”

Section: Introductionmentioning

confidence: 99%

“…The model then was used to develop an efficient data allocation algorithms [20]. Then we [23,24] developed a transient model for Jackson networks and showed to what extent the steady-state model can be used. However, there is a computational problem in attempting to use this model for large systems.…”

Section: Introductionmentioning

confidence: 99%

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Modeling parallel and distributed systems with finite workloads

Mohamed

Lipsky

Ammar

2005

Performance Evaluation

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Modeling parallel and distributed systems with finite workloads

Mohamed

Lipsky

Ammar

2005

Performance Evaluation

Self Cite

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“…However, there is a computational problem in attempting to use this model for large systems. An approximation to the transient model using the steady state solution was presented to overcome such problems when dealing with large systems [17].…”

Section: Introductionmentioning

confidence: 99%

Modeling parallel and distributed systems with finite workloads

Mohamed

Lipsky

Ammar

18th International Parallel and Distributed Processing Symposium, 2004. Proceedings.

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In studying or designing parallel and distributed systems one should have available a robust analytical model that includes the major parameters that determines the system performance. Jackson networks have been very successful in modeling parallel and distributed systems. However, the ability of Jackson networks to predict performance with system changes remains an open question, since they do not apply to systems where there are population size constraints.Also, the product-form solution of Jackson networks assumes steady state and exponential service centers or certain specialized queueing disciplines. In this paper, we present a transient model for Jackson networks that is applicable to any population size and any finite workload (no new arrivals). Using several Erlangian and Hyperexponential distributions we show to what extent the exponential distribution can be used to approximate other distributions and transient systems with finite workloads. When the number of tasks to be executed is large enough, the model approaches the product-form solution (steady state solution). We also, study the case where the nonexponential servers have queueing (Jackson networks can't be applied). Finally, we show how to use the model to analyze the performance of parallel and distributed systems.

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