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Gerald Jay Sussman. Jacobi, Ian Campbell Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science 2010-12-06T16:36:54Z 2010-12-06T16:36:54Z 2010 2010 http://hdl.handle.net/1721.1/60101 679661122 Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010. This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. Cataloged from student submitted PDF version of thesis. Includes bibliographical references (p. 93-96). Is it possible to construct a heterogeneous distributed computing architecture capable of solving interesting complex problems? Can we easily use this architecture to maintain a detailed history or provenance of the data processed by it? Most existing distributed architectures can perform only one operation at a time. While they are capable of tracing possession of data, these architectures do not always track the network of operations used to synthesize new data. This thesis presents a distributed implementation of data propagation, a computational model that provides for concurrent processing that is not constrained to a single distributed operation. This system is capable of distributing computation across a heterogeneous network. It allows for the division of multiple simultaneous operations in a single distributed system. I also identify four constraints that may be placed on general-purpose data propagation to allow for deterministic computation in such a distributed propagation network. This thesis also presents an application of distributed propagation by illustrating how a generic transformation may be applied to existing propagator networks to allow for the maintenance of data provenance. I show that the modular structure of data propagation permits the simple modification of a propagator network design to maintain the histories of data. by Ian Campbell Jacobi. S.M. 96 p. eng Massachusetts Institute of Technology M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 Electrical Engineering and Computer Science. Constructing provenance-aware distributed systems with data propagation Thesis application/pdf false Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="15e7ebf2-0ba2-4f16-a469-e090978a448b"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Constructing provenance-aware distributed systems with data propagation</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2010</PublicationDate> <Authors> <Author> <DisplayName>Jacobi, Ian Campbell</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://dspace.mit.edu/handle/1721.1/7582</License> <Keyword>Electrical Engineering and Computer Science.</Keyword> <Abstract>Is it possible to construct a heterogeneous distributed computing architecture capable of solving interesting complex problems? Can we easily use this architecture to maintain a detailed history or provenance of the data processed by it? Most existing distributed architectures can perform only one operation at a time. While they are capable of tracing possession of data, these architectures do not always track the network of operations used to synthesize new data. This thesis presents a distributed implementation of data propagation, a computational model that provides for concurrent processing that is not constrained to a single distributed operation. This system is capable of distributing computation across a heterogeneous network. It allows for the division of multiple simultaneous operations in a single distributed system. I also identify four constraints that may be placed on general-purpose data propagation to allow for deterministic computation in such a distributed propagation network. This thesis also presents an application of distributed propagation by illustrating how a generic transformation may be applied to existing propagator networks to allow for the maintenance of data provenance. I show that the modular structure of data propagation permits the simple modification of a propagator network design to maintain the histories of data.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>