Matrix representations and analytical solution methods for stochastic activity networks

Persistent Link:
http://hdl.handle.net/10150/278660
Title:
Matrix representations and analytical solution methods for stochastic activity networks
Author:
Tvedt, Janet Elaine, 1963-
Issue Date:
1990
Publisher:
The University of Arizona.
Rights:
Copyright © 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.
Abstract:
Stochastic activity networks, a probabilistic extension of Petri nets, can be used to evaluate the performance, dependability, and performability of a wide variety of systems. When analytical solution methods are used, it is necessary to generate a state-level representation of a model prior to solution. The transition-rate matrices obtained from this representation tend to be very large and sparse. Analytical solutions to such problems can only be obtained by exploiting the matrix sparsity both in storage and computation. We do this, by studying alternative matrix representation schemes and steady-state and transient solution methods, and implementing methods appropriate for problems of this type. The results suggest that the implemented techniques can yield analytical solutions for many realistic models of computer systems and networks. This is evidenced by the performance evaluation of a CSMA/CD Local area network.
Type:
text; Thesis-Reproduction (electronic)
Keywords:
Engineering, Electronics and Electrical.; Operations Research.; Computer Science.
Degree Name:
M.S.
Degree Level:
masters
Degree Program:
Graduate College
Degree Grantor:
University of Arizona
Advisor:
Sanders, William H.

Full metadata record

DC FieldValue Language
dc.language.isoen_USen_US
dc.titleMatrix representations and analytical solution methods for stochastic activity networksen_US
dc.creatorTvedt, Janet Elaine, 1963-en_US
dc.contributor.authorTvedt, Janet Elaine, 1963-en_US
dc.date.issued1990en_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.description.abstractStochastic activity networks, a probabilistic extension of Petri nets, can be used to evaluate the performance, dependability, and performability of a wide variety of systems. When analytical solution methods are used, it is necessary to generate a state-level representation of a model prior to solution. The transition-rate matrices obtained from this representation tend to be very large and sparse. Analytical solutions to such problems can only be obtained by exploiting the matrix sparsity both in storage and computation. We do this, by studying alternative matrix representation schemes and steady-state and transient solution methods, and implementing methods appropriate for problems of this type. The results suggest that the implemented techniques can yield analytical solutions for many realistic models of computer systems and networks. This is evidenced by the performance evaluation of a CSMA/CD Local area network.en_US
dc.typetexten_US
dc.typeThesis-Reproduction (electronic)en_US
dc.subjectEngineering, Electronics and Electrical.en_US
dc.subjectOperations Research.en_US
dc.subjectComputer Science.en_US
thesis.degree.nameM.S.en_US
thesis.degree.levelmastersen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.advisorSanders, William H.en_US
dc.identifier.proquest1342682en_US
dc.identifier.bibrecord.b26593051en_US
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