Self-similarity through high-variability: statistical analysis of Ethernet LAN traffic at the source level

Willinger, Walter; Taqqu, Murad S.; Sherman, Robert P.; Wilson, Daniel V.

doi:10.1109/90.554723

Cited by 1,369 publications

(918 citation statements)

References 30 publications

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“…Again, each process has periods of activity that come from a heavy-tailed distribution. The difference is that each process alternates between on and off periods, rather than contributing a single on period [730,155,678,303].…”

Section: Merged On-off Processesmentioning

confidence: 99%

“…In fact, the self-similarity depends on a single parameter, α: the tail index of the distribution of on (or off ) times. This should be chosen from the range 1 < α < 2, and leads to self-similarity with H = 3−α 2 [730,678]. Moreover, the minimal α dominates the process, so different sources may actually have different values of α, and some may even have finite variance (that is, their on and off times are not heavy-tailed).…”

Section: Merged On-off Processesmentioning

confidence: 99%

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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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Section: Merged On-off Processesmentioning

confidence: 99%

Section: Merged On-off Processesmentioning

confidence: 99%

Workload Modeling for Computer Systems Performance Evaluation

Feitelson

2015

191

131

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“…A plausible physical explanation for the occurrence of Self-Similarity in high speed network traffic is explained in [12] is based on convergence results for processes that exhibit high variability.…”

Section: Existence Reason Of Self-similaritymentioning

confidence: 99%

Self-Similarity and modeling of LTE/LTE-A data traffic

Polaganga

Liang

2015

Measurement

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“…Therefore, the user behavior is modeled as a bursty two-state ON/OFF process, where ON periods correspond to the transfer of Web objects, and OFF periods correspond to the silent intervals after that all objects in a Web page have been retrieved. It has been demonstrated that the superposition of a large number of ON/OFF sources results in self-similar traffic, if the durations of ON and OFF phases are described by heavy-tailed distributions [12,43]. The characteristics of the request stream are specified through heavy-tailed distributions as regarding file size, request size, file popularity, embedded object references, temporal locality, and OFF times.…”

Section: Comparison Of Selected Toolsmentioning

confidence: 99%

Benchmarking Models and Tools for Distributed Web-Server Systems

Andreolini

Cardellini

Colajanni

2002

Performance Evaluation of Complex Systems: Techniques and Tools

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Abstract. This tutorial reviews benchmarking tools and techniques that can be used to evaluate the performance and scalability of highly accessed Web-server systems. The focus is on design and testing of locally and geographically distributed architectures where the performance evaluation is obtained through workload generators and analyzers in a laboratory environment. The tutorial identifies the qualities and issues of existing tools with respect to the main features that characterize a benchmarking tool (workload representation, load generation, data collection, output analysis and report) and their applicability to the analysis of distributed Web-server systems.

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Self-similarity through high-variability: statistical analysis of Ethernet LAN traffic at the source level

Cited by 1,369 publications

References 30 publications

Workload Modeling for Computer Systems Performance Evaluation

Workload Modeling for Computer Systems Performance Evaluation

Self-Similarity and modeling of LTE/LTE-A data traffic

Benchmarking Models and Tools for Distributed Web-Server Systems

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