Mean Value Analysis Approximation for multiple server queueing networks

Akyildiz, Ian F.; Bolch, Gunter

doi:10.1016/0166-5316(88)90015-6

Cited by 20 publications

(5 citation statements)

References 18 publications

(22 reference statements)

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“…Linearizer [41]. The authors in [63] and [64] address this limitation by fixed point interpolations, for models that include multi-server nodes. However, these methods do not address the LLD case in full generality.…”

Section: State-of-the-artmentioning

confidence: 99%

Facilitating load-dependent queueing analysis through factorization

Casale

Harrison

Ong

2021

Performance Evaluation

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Section: State-of-the-artmentioning

confidence: 99%

Facilitating load-dependent queueing analysis through factorization

Casale

Harrison

Ong

2021

Performance Evaluation

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“…Approximate MVA models for closed QNs with multipleserver queuing stations were developed in [1], [20], [22]. These models consider that all resources in a multi-server queuing station have the same processing speed regardless of concurrency level and do not consider the effects of memory contention.…”

Section: Related Workmentioning

confidence: 99%

Predicting the Effect of Memory Contention in Multi-Core Computers Using Analytic Performance Models

Bardhan

Menascé

2015

IEEE Trans. Comput.

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Analyzing and predicting the performance of applications that run on multi-core computers is essential. This paper demonstrates experimentally that memory contention resulting from multiple cores accessing shared memory resources can become a significant component (i.e., over 50 percent) of an application's execution time. The paper develops single-and multi-class analytic performance models for predicting the effect of memory contention on a job's execution time. The models consider local and remote memory as in NUMA architectures. Model validation was done using a micro-benchmark and programs from HBench, UnixBench, and SPECCPU2006 running on machines with 4, 12, and 16 cores. The paper shows how to derive the model parameters and demonstrates that there is a significant difference in predicted values when memory contention is ignored. For example, a model that ignores memory contention predicts an average execution time about four times smaller than the experimental value for a concurrency level of 18 while the model with memory contention predicts a value that is 90 percent of the experimental value for the same concurrency level.

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“…Modified-vacation intervals theory was used to get approximate solution [4] . Mean value analysis (MVA) is the method which was used to solve multi-class priority open and closed queueing networks [5,6,7] . Reiser's work on analysis of Reduced-work rate assumption was proven as effective and accurate [8] .…”

Section: Introductionmentioning

confidence: 99%

Analysis on Aircraft Sortie Generation Rate Based on Multi-class Closed Queueing Network

Zheng¹,

Wang²,

Wang³

et al. 2013

Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)

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In order to research the sortie generation rate (SGR) of carrier-based aircrafts, an analytical method based on closed queueing network was put forward. A multi-class, multi-server non-preemptive (or Head of Line, HOL) closed queueing network model was analyzed. As the exact mathematical solution is not available, an approximate method based on reduced work-load assumption and mean value analysis (MVA) iteration was used to gain the performance of the network. As a result, this approximation method can provide the marginal distribution of customers at each service facility of the queueing network. Numerical results that show that the accuracy of the method is good was given.

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Mean Value Analysis Approximation for multiple server queueing networks

Cited by 20 publications

References 18 publications

Facilitating load-dependent queueing analysis through factorization

Facilitating load-dependent queueing analysis through factorization

Predicting the Effect of Memory Contention in Multi-Core Computers Using Analytic Performance Models

Analysis on Aircraft Sortie Generation Rate Based on Multi-class Closed Queueing Network

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