Comparison and scaling methods for performance analysis of stochastic networks

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en Leskelä, Lasse 2012-02-17T07:22:09Z 2012-02-17T07:22:09Z 2005-12-02
dc.identifier.isbn 951-22-7952-5
dc.identifier.issn 0784-3143
dc.description.abstract Stochastic networks are mathematical models for traffic flows in networks with uncertainty. The goal of this thesis is to develop new methods for analyzing performance and stability of stochastic networks, helping to better understand and control uncertainty in complex distributed systems. The thesis considers three instances of stochastic networks, each representing a specific challenge for analytical modeling. The first case studies the impact of incomplete information to a queueing network with distributed admission control. Stability conditions for various admission policies are derived, together with a numerical algorithm for performance evaluation. In the second case, stochastic comparison is used to derive performance bounds for multiclass loss networks with overflow routing. The third model is a spatial random field generated by a large number of noninteracting sources, for which scaling and renormalization are used to show how the level of randomness of the individual sources may critically affect the macroscopic statistical properties of the field. The results of the thesis illustrate the feasibility of stochastic comparison and stochastic analysis in deriving approximations and performance bounds for complex physical networks with uncertainty. Approximations and performance bounds based on exact mathematical methods have the advantage that they explicitly state the type of circumstances required for the accuracy of the estimates. The resulting analytical formulas can sometimes reveal interesting properties that are not easily detected using numerical simulation. en
dc.format.extent 20, [47]
dc.format.mimetype application/pdf
dc.language.iso en en
dc.publisher Helsinki University of Technology en
dc.publisher Teknillinen korkeakoulu fi
dc.relation.ispartofseries Research reports / Helsinki University of Technology, Institute of Mathematics. A en
dc.relation.ispartofseries 491 en
dc.relation.haspart Leskelä, L. (2006). Stabilization of an overloaded queueing network using measurement-based admission control. Journal of Applied Probability 43 (1), to appear, 14 pages. [article1.pdf] © 2006 Applied Probability Trust. By permission.
dc.relation.haspart Leskelä, L. and Resing, J. (2004). A tandem queueing network with feedback admission control. Institut Mittag-Leffler Report No. 09, 2004/2005, fall, 9 pages. [article2.pdf] © 2004 by authors.
dc.relation.haspart George, L., Jonckheere, M. and Leskelä, L. (2005). Does repacking improve performance of multiclass loss networks with overflow routing? In: X. Liang, Z. Xin, V. B. Iversen, G. S. Kuo (Eds.), Proceedings of the 19th International Teletraffic Congress. Beijing University of Posts and Telecommunications Press, pp. 1365-1373. [article3.pdf] © 2005 by authors.
dc.relation.haspart Kaj, I., Leskelä, L., Norros, I. and Schmidt, V. (2005). Scaling limits for random fields with long-range dependence. Institut Mittag-Leffler Report No. 24, 2004/2005, fall, 25 pages. [article4.pdf] © 2005 by authors.
dc.subject.other Mathematics en
dc.title Comparison and scaling methods for performance analysis of stochastic networks en
dc.type G5 Artikkeliväitöskirja fi
dc.description.version reviewed en
dc.contributor.department Department of Engineering Physics and Mathematics en
dc.contributor.department Teknillisen fysiikan ja matematiikan osasto fi
dc.subject.keyword stochastic network en
dc.subject.keyword queueing en
dc.subject.keyword admission control en
dc.subject.keyword overflow routing en
dc.subject.keyword stochastic comparison en
dc.subject.keyword scaling en
dc.subject.keyword renormalization en
dc.subject.keyword spatial random field en
dc.identifier.urn urn:nbn:fi:tkk-005940
dc.type.dcmitype text en
dc.type.ontasot Väitöskirja (artikkeli) fi
dc.type.ontasot Doctoral dissertation (article-based) en
dc.contributor.lab Institute of Mathematics en
dc.contributor.lab Matematiikan laitos fi

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