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dc.contributor.authorCarrasco, Juan A.
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Enginyeria Electrònica
dc.date.accessioned2013-08-01T07:20:41Z
dc.date.available2013-11-28T07:53:51Z
dc.date.created2011
dc.date.issued2011
dc.identifier.citationCarrasco, J. An efficient and numerically stable method for computing bounds for the interval availability distribution. "Informs journal on computing", 2011, vol. 23, núm. 2, p. 268-283.
dc.identifier.issn1091-9856
dc.identifier.urihttp://hdl.handle.net/2117/20049
dc.description.abstractThis paper is concerned with the computation of the interval availability (proportion of time in a time interval in which the system is up) distribution of a fault-tolerant system modeled by a finite (homogeneous) continuous-time Markov chain (CTMC). General-purpose methods for performing that computation tend to be very expensive when the CTMC and the time interval are large. Based on a previously available method (regenerative transformation) for computing the interval availability complementary distribution, we develop a method called bounding regenerative transformation for the computation of bounds for that measure. Similar to regenerative transformation, bounding regenerative transformation requires the selection of a regenerative state. The method is targeted at a certain class of models, including both exact and bounding failure/repair models of fault-tolerant systems with increasing structure function, with exponential failure and repair time distributions and repair in every state with failed components having failure rates much smaller than repair rates (F/R models), with a “natural” selection for the regenerative state. The method is numerically stable and computes the bounds with well-controlled error. For models in the targeted class and the natural selection for the regenerative state, computational cost should be traded off with bounds tightness through a control parameter. For large models in the class, the version of the method that should have the smallest computational cost should have small computational cost relative to the model size if the value above which the interval availability has to be guaranteed to be is close to 1. In addition, under additional conditions satisfied by F/R models, the bounds obtained with the natural selection for the regenerative state by the version that should have the smallest computational cost seem to be tight for all time intervals or not small time intervals, depending on whether the initial probability distribution of the CTMC is concentrated in the regenerative state or not.
dc.format.extent16 p.
dc.language.isoeng
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica
dc.subject.lcshMarkov processes
dc.titleAn efficient and numerically stable method for computing bounds for the interval availability distribution
dc.typeArticle
dc.subject.lemacMarkov, Processos de
dc.contributor.groupUniversitat Politècnica de Catalunya. QINE - Disseny de Baix Consum, Test, Verificació i Circuits Integrats de Seguretat
dc.identifier.doi10.1287/ijoc.1100.0399
dc.relation.publisherversionhttp://joc.journal.informs.org/cgi/search?fulltext=CARRASCO&sendit=Enter&volume=23&issue=2&journalcode=joc
dc.rights.accessOpen Access
local.identifier.drac5781124
dc.description.versionPostprint (published version)
local.citation.authorCarrasco, J.
local.citation.publicationNameInforms journal on computing
local.citation.volume23
local.citation.number2
local.citation.startingPage268
local.citation.endingPage283


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