Efficient estimation of the probability of extreme cell delays

dc.contributor.author	Lamothe, Gilles
dc.date.accessioned	2013-11-08T13:58:35Z
dc.date.available	2013-11-08T13:58:35Z
dc.date.created	2004
dc.date.issued	2004
dc.degree.level	Doctoral
dc.description.abstract	We wish to estimate the probability of extreme cell delays for a particular virtual connection (VC) or virtual path (VP) in an Asynchronous Transfer Mode (ATM) network. Since extreme cell delays are rare events we cannot efficiently estimate the probability of extreme cell delays using crude Monte-Carlo methods. We increase (exponentially twist) the workload of a related Markov additive chain, which we call the encumbrance, and use the A-cycle sampling technique to analyse switches with finite buffers multiplexing cells from Bernoulli interrupted sources with constant bit rate during bursts.
dc.format.extent	127 p.
dc.identifier.citation	Source: Dissertation Abstracts International, Volume: 66-05, Section: B, page: 2619.
dc.identifier.uri	http://hdl.handle.net/10393/29130
dc.identifier.uri	http://dx.doi.org/10.20381/ruor-12784
dc.language.iso	en
dc.publisher	University of Ottawa (Canada)
dc.subject.classification	Mathematics.
dc.title	Efficient estimation of the probability of extreme cell delays
dc.type	Thesis

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