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dc.contributor.advisorSanders, Williamen_US
dc.contributor.authorFreire, Roberto, 1960-
dc.creatorFreire, Roberto, 1960-en_US
dc.date.accessioned2013-04-03T13:25:26Z
dc.date.available2013-04-03T13:25:26Z
dc.date.issued1990en_US
dc.identifier.urihttp://hdl.handle.net/10150/278460
dc.description.abstractStochastic activity networks (SANs) have been used in the modeling of computer systems because of their suitability in representing distributed systems. SANs may be solved by analysis or by simulation. When simulation is used, future events list management is very time consuming, as with other simulation techniques. New methods that take advantage of the SAN model structure are presented which significantly reduce the cost of future events list management. Multiple future events lists are used to reduce operations required upon each state change.
dc.language.isoen_USen_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.subjectEngineering, Electronics and Electrical.en_US
dc.subjectEngineering, System Science.en_US
dc.subjectComputer Science.en_US
dc.titleA technique for simulating composed SAN-based reward modelsen_US
dc.typetexten_US
dc.typeThesis-Reproduction (electronic)en_US
thesis.degree.grantorUniversity of Arizonaen_US
thesis.degree.levelmastersen_US
dc.identifier.proquest1342649en_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.nameM.S.en_US
dc.identifier.bibrecord.b26592216en_US
refterms.dateFOA2018-06-15T09:25:56Z
html.description.abstractStochastic activity networks (SANs) have been used in the modeling of computer systems because of their suitability in representing distributed systems. SANs may be solved by analysis or by simulation. When simulation is used, future events list management is very time consuming, as with other simulation techniques. New methods that take advantage of the SAN model structure are presented which significantly reduce the cost of future events list management. Multiple future events lists are used to reduce operations required upon each state change.


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