Difficulties in simulating queues with Pareto service

Gross, Donald; Shortle, John; Fischer, Martin J.; Masi, D.M. Bevilacqua

doi:10.1109/wsc.2002.1172911

Cited by 26 publications

(17 citation statements)

References 3 publications

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“…This is in spirit of the suggestion in the paper "Difficulties in simulating queues with Pareto service" [10] that says: "Since for any finite simulation run length, there is always a maximum value of the random variables generated, we, in actuality, are simulating a truncated Pareto service distribution. It has also been argued that there is always a maximum file size or claim amount so, in reality, we are always dealing with truncated distributions."…”

Section: Simulation Involving Flows With Heavy Tailed Size Distributionmentioning

confidence: 98%

Simulating Flow Level Bandwidth Sharing with Pareto distributed File Sizes

Rojas-Mora¹,

Jiménez²,

Altman³

2011

Proceedings of the 5th International ICST Conference on Performance Evaluation Methodologies and Tools

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Our goal is to achieve deeper understanding of the limitation of queueing models, on one hand, and of common simulation practice, on the other hand, as tools for predicting performance of bandwidth sharing between competing TCP flows. In particular, we (i) present an overview of simulation problems that are expected to arise due to the very heavy tail of the distribution of the size of TCP flows, and (ii) through simulations we show that the average sojourn time of competing flows are quite sensitive to various network parameters. The understanding that we get from the first point allows us to better assess when are the conclusions from simulation results on bandwidth sharing reliable.Using simulations in ns2, we study bandwidth sharing under various load factors and show the benefit of using bootstrap as a post simulation tool for analyzing the simulation results.

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Section: Simulation Involving Flows With Heavy Tailed Size Distributionmentioning

confidence: 98%

Simulating Flow Level Bandwidth Sharing with Pareto distributed File Sizes

Rojas-Mora¹,

Jiménez²,

Altman³

2011

Proceedings of the 5th International ICST Conference on Performance Evaluation Methodologies and Tools

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“…This means that occasionally something "big" happens, which distorts the statistics of the workload seen before it occurred. Thus the workload is always in a transient condition [157,306], meaning that:…”

Section: Stationarity In Workloadsmentioning

confidence: 99%

“…Even if the mean is in fact finite (which happens if the tail index satisfies a > 1), convergence may be very slow. In practice, the borderline between convergence and lack thereof is not sharp [157,306,301]. Very close to the borderline, an extremely large number of samples may be needed in order to converge to the true value.…”

Section: The Law Of Large Numbersmentioning

confidence: 99%

See 1 more Smart Citation

Workload Modeling for Computer Systems Performance Evaluation

Feitelson

2015

191

131

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Reliable performance evaluations require the use of representative workloads. This is no easy task since modern computer systems and their workloads are complex, with many interrelated attributes and complicated structures. Experts often use sophisticated mathematics to analyze and describe workload models, making these models difficult for practitioners to grasp. This book aims to close this gap by emphasizing the intuition and the reasoning behind the definitions and derivations related to the workload models. It provides numerous examples from real production systems, with hundreds of graphs. Using this book, readers will be able to analyze collected workload data and clean it if necessary, derive statistical models that include skewed marginal distributions and correlations, and consider the need for generative models and feedback from the system. The descriptive statistics techniques covered are also useful for other domains.

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“…In [16], in order to improve the TAM, Fischer et al proposed modifications to the version asserted by Harris et al in [15]. Shortle also presents in [17] some difficulties related to the simulation of queues with service time defined by the Pareto distribution.…”

Section: B Treating Long-range Dependent Trafficmentioning

confidence: 99%

Pragmatic Approach For Estimating Wireless Broadband Traffic Using the Theory of Large Deviations

Hisatugu¹,

Garcia²

2012

Journal of Communication and Information Systems

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Abstract-This paper proposes a methodology to predict wireless broadband network capacity based on effective bandwidth estimation. Former wireless network planning strategies were based on the estimation of the distribution of the number of users over the mobile network area. However, with the rapid spreading of wireless broadband networks and the increased number of services, the characteristics of user traffic have become an important matter due to the uniqueness of user profile. Furthermore, new wireless broadband networks are no longer based on circuit switching, but on packet switching technology. This paper applies the Large Deviations Theory to leverage estimation of the aggregated traffic intensity of several users. The approach was validated by analyzing known traffic traces of wireless broadband networks.Index Terms-wireless broadband, effective bandwidth, capacity planning, aggregated traffic, mobility model.

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Difficulties in simulating queues with Pareto service

Cited by 26 publications

References 3 publications

Simulating Flow Level Bandwidth Sharing with Pareto distributed File Sizes

Simulating Flow Level Bandwidth Sharing with Pareto distributed File Sizes

Workload Modeling for Computer Systems Performance Evaluation

Pragmatic Approach For Estimating Wireless Broadband Traffic Using the Theory of Large Deviations

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