Probabilistic sequential machine modeling of computer systems and its application to error detection

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dc.contributor.advisorLee, Samuel C.
dc.contributor.committeeMemberPaskusz, Gerhard F.
dc.contributor.committeeMemberChen, Chih-Fan
dc.contributor.committeeMemberJohnson, Olin G.
dc.contributor.committeeMemberHuang, Jung-Chang
dc.contributor.committeeMemberBarr, Betty J.
dc.creatorAsai, Hitohisa
dc.date.accessioned2022-07-27T16:30:20Z
dc.date.available2022-07-27T16:30:20Z
dc.date.issued1975
dc.description.abstractThe problems of computer system modeling and of error detection in a computer system are investigated in this research. Probabilistic sequential machine modeling of a computer system is proposed by considering input/output flexibilities on the probabilistic sequential machine theory. With the model, a theoretical approach and a practical approach to error detection are presented. In the theoretical approach, a two-state isolated machine, which contains the well-known completely isolated machine as a subset, is constructed, and a decomposition method of a probabilistic sequential machine into two-state probabilistic sequential machines is studied. Based on the isolated machine and the decomposition method, properties of the isolated machine (which consists of states more than two), such as input traceability, past subsystem activity distribution, and the initial state distribution independence, etc., are discussed. Traceback properties of the machine are used for error detection. From distribution of input types to and output channel activities from a computer system, the probability of subsystem activities in a steady state is determined in the practical approach by an optimization of a non-linear programming problem. The nonlinear programming problem is formulated with two phases, a calibration and a monitoring of the computer system. Next, the most likely subsystem which contains an error is determined. A probabilistic sequential machine model of a computer system is built. The advantages of the practical approach are demonstrated on the model which is simulated in a normal computer operation.
dc.description.departmentEngineering, Cullen College of
dc.format.digitalOriginreformatted digital
dc.format.mimetypeapplication/pdf
dc.identifier.other2404360
dc.identifier.urihttps://hdl.handle.net/10657/10614
dc.language.isoen
dc.rightsThis item is protected by copyright but is made available here under a claim of fair use (17 U.S.C. Section 107) for non-profit research and educational purposes. Users of this work assume the responsibility for determining copyright status prior to reusing, publishing, or reproducing this item for purposes other than what is allowed by fair use or other copyright exemptions. Any reuse of this item in excess of fair use or other copyright exemptions requires express permission of the copyright holder.
dc.titleProbabilistic sequential machine modeling of computer systems and its application to error detection
dc.type.dcmiText
dc.type.genreThesis
thesis.degree.collegeCullen College of Engineering
thesis.degree.departmentEngineering, Cullen College of
thesis.degree.disciplineElectrical Engineering
thesis.degree.grantorUniversity of Houston
thesis.degree.levelDoctoral
thesis.degree.nameDoctor of Philosophy

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