ServerModels for Probabilistic Network Calculus

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

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  • Norwegian University of Science and Technology (NTNU)
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Details

Original languageEnglish
Title of host publicationINFORMATIK 2005 - Informatik LIVE!, Beitrage der 35. Jahrestagung der Gesellschaft fur Informatik e.V. (GI)
Pages400-404
Number of pages5
Publication statusPublished - 2005
Externally publishedYes
Event35th Jahrestagung der Gesellschaft fur Informatik e.V. (GI): Informatik LIVE!, INFORMATIK 200535th Annual Conference of the German Informatics Society (GI): Informatics LIVE!,INFORMATIK 2005 - Bonn, Germany
Duration: 19 Sept 200522 Sept 2005

Publication series

NameINFORMATIK 2005 - Informatik LIVE!, Beitrage der 35. Jahrestagung der Gesellschaft fur Informatik e.V. (GI)
Volume1

Abstract

Network calculus is a deterministic queuing theory that has gained increasing attention in recent time. Founded on min-plus algebra it resorts to intuitive convolution formulae for efficient concatenation of servers and derivation of related performance bounds. Yet, the pessimistic worst-case analysis of deterministic network calculus gave rise to probabilistic counterparts that aim at utilizing the smoothing effects of statistical multiplexing by allowing for certain violation probabilities. Related theories are, however, significantly more complicated and still subject to research. To advance theory this paper evolves server models for probabilistic network calculus that are based on moment generating functions to efficiently utilize statistical multiplexing and the independence of flows.

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Cite this

ServerModels for Probabilistic Network Calculus. / Fidler, Markus.
INFORMATIK 2005 - Informatik LIVE!, Beitrage der 35. Jahrestagung der Gesellschaft fur Informatik e.V. (GI). 2005. p. 400-404 (INFORMATIK 2005 - Informatik LIVE!, Beitrage der 35. Jahrestagung der Gesellschaft fur Informatik e.V. (GI); Vol. 1).

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

Fidler, M 2005, ServerModels for Probabilistic Network Calculus. in INFORMATIK 2005 - Informatik LIVE!, Beitrage der 35. Jahrestagung der Gesellschaft fur Informatik e.V. (GI). INFORMATIK 2005 - Informatik LIVE!, Beitrage der 35. Jahrestagung der Gesellschaft fur Informatik e.V. (GI), vol. 1, pp. 400-404, 35th Jahrestagung der Gesellschaft fur Informatik e.V. (GI): Informatik LIVE!, INFORMATIK 200535th Annual Conference of the German Informatics Society (GI): Informatics LIVE!,INFORMATIK 2005, Bonn, Germany, 19 Sept 2005. <https://dl.gi.de/bitstream/handle/20.500.12116/28069/GI-Proceedings.67-90.pdf?sequence=1&isAllowed=y>
Fidler, M. (2005). ServerModels for Probabilistic Network Calculus. In INFORMATIK 2005 - Informatik LIVE!, Beitrage der 35. Jahrestagung der Gesellschaft fur Informatik e.V. (GI) (pp. 400-404). (INFORMATIK 2005 - Informatik LIVE!, Beitrage der 35. Jahrestagung der Gesellschaft fur Informatik e.V. (GI); Vol. 1). https://dl.gi.de/bitstream/handle/20.500.12116/28069/GI-Proceedings.67-90.pdf?sequence=1&isAllowed=y
Fidler M. ServerModels for Probabilistic Network Calculus. In INFORMATIK 2005 - Informatik LIVE!, Beitrage der 35. Jahrestagung der Gesellschaft fur Informatik e.V. (GI). 2005. p. 400-404. (INFORMATIK 2005 - Informatik LIVE!, Beitrage der 35. Jahrestagung der Gesellschaft fur Informatik e.V. (GI)).
Fidler, Markus. / ServerModels for Probabilistic Network Calculus. INFORMATIK 2005 - Informatik LIVE!, Beitrage der 35. Jahrestagung der Gesellschaft fur Informatik e.V. (GI). 2005. pp. 400-404 (INFORMATIK 2005 - Informatik LIVE!, Beitrage der 35. Jahrestagung der Gesellschaft fur Informatik e.V. (GI)).
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title = "ServerModels for Probabilistic Network Calculus",
abstract = "Network calculus is a deterministic queuing theory that has gained increasing attention in recent time. Founded on min-plus algebra it resorts to intuitive convolution formulae for efficient concatenation of servers and derivation of related performance bounds. Yet, the pessimistic worst-case analysis of deterministic network calculus gave rise to probabilistic counterparts that aim at utilizing the smoothing effects of statistical multiplexing by allowing for certain violation probabilities. Related theories are, however, significantly more complicated and still subject to research. To advance theory this paper evolves server models for probabilistic network calculus that are based on moment generating functions to efficiently utilize statistical multiplexing and the independence of flows.",
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