Statistical End-to-end Performance Bounds for Networks under Long Memory FBM Cross Traffic

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Original languageEnglish
Title of host publication2010 IEEE 18th International Workshop on Quality of Service
Subtitle of host publication IWQoS 2010
Publication statusPublished - Aug 2010
Event2010 IEEE 18th International Workshop on Quality of Service, IWQoS 2010 - Beijing, China
Duration: 16 Jun 201018 Jun 2010

Publication series

NameIEEE International Workshop on Quality of Service, IWQoS
ISSN (Print)1548-615X

Abstract

Fractional Brownian motion (fBm) became known as a useful model for Internet traffic incorporating its self-similar and long-range dependent properties. In this paper we derive end-to-end performance bounds for a through flow in a network of tandem queues under fBm cross traffic. We build on a previously derived sample path envelope for fBm, which possesses aWeibullian decay of overflow probabilities.We employ the sample path envelope and the concept of leftover service curves to model the remaining service after scheduling fBm cross traffic at a system. Using composition results for tandem systems from the stochastic network calculus we derive endto- end statistical performance bounds for individual flows in networks under fBm cross traffic. We discover that these bounds grow in O (n(log n) 1/2-2H) for n systems in series where H is the Hurst parameter of the fBm cross traffic. We show numerical results on the impact of the variability and the correlation of fBm traffic on network performance.

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Statistical End-to-end Performance Bounds for Networks under Long Memory FBM Cross Traffic. / Rizk, Amr; Fidler, Markus.
2010 IEEE 18th International Workshop on Quality of Service: IWQoS 2010. 2010. 5542748 (IEEE International Workshop on Quality of Service, IWQoS).

Research output: Chapter in book/report/conference proceedingConference contributionResearchpeer review

Rizk, A & Fidler, M 2010, Statistical End-to-end Performance Bounds for Networks under Long Memory FBM Cross Traffic. in 2010 IEEE 18th International Workshop on Quality of Service: IWQoS 2010., 5542748, IEEE International Workshop on Quality of Service, IWQoS, 2010 IEEE 18th International Workshop on Quality of Service, IWQoS 2010, Beijing, China, 16 Jun 2010. https://doi.org/10.1109/IWQoS.2010.5542748
Rizk, A., & Fidler, M. (2010). Statistical End-to-end Performance Bounds for Networks under Long Memory FBM Cross Traffic. In 2010 IEEE 18th International Workshop on Quality of Service: IWQoS 2010 Article 5542748 (IEEE International Workshop on Quality of Service, IWQoS). https://doi.org/10.1109/IWQoS.2010.5542748
Rizk A, Fidler M. Statistical End-to-end Performance Bounds for Networks under Long Memory FBM Cross Traffic. In 2010 IEEE 18th International Workshop on Quality of Service: IWQoS 2010. 2010. 5542748. (IEEE International Workshop on Quality of Service, IWQoS). Epub 2009 Sept 3. doi: 10.1109/IWQoS.2010.5542748
Rizk, Amr ; Fidler, Markus. / Statistical End-to-end Performance Bounds for Networks under Long Memory FBM Cross Traffic. 2010 IEEE 18th International Workshop on Quality of Service: IWQoS 2010. 2010. (IEEE International Workshop on Quality of Service, IWQoS).
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abstract = "Fractional Brownian motion (fBm) became known as a useful model for Internet traffic incorporating its self-similar and long-range dependent properties. In this paper we derive end-to-end performance bounds for a through flow in a network of tandem queues under fBm cross traffic. We build on a previously derived sample path envelope for fBm, which possesses aWeibullian decay of overflow probabilities.We employ the sample path envelope and the concept of leftover service curves to model the remaining service after scheduling fBm cross traffic at a system. Using composition results for tandem systems from the stochastic network calculus we derive endto- end statistical performance bounds for individual flows in networks under fBm cross traffic. We discover that these bounds grow in O (n(log n) 1/2-2H) for n systems in series where H is the Hurst parameter of the fBm cross traffic. We show numerical results on the impact of the variability and the correlation of fBm traffic on network performance.",
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