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Steve Ward. Paluska, Justin Mazzola, 1981- Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science 2012-07-02T14:17:56Z 2012-07-02T14:17:56Z 2012 2012 http://hdl.handle.net/1721.1/71275 795194456 Thesis (Elec. E. in Computer Science)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012. 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. 57-58). We describe an approach to automate certain high-level implementation decisions in a pervasive application, allowing them to be postponed until run time. Our system enables a model in which an application programmer can specify the behavior of an adaptive application as a set of open-ended decision points. We formalize decision points as Goals, each of which may be satisfied by a set of scripts called Techniques. The set of Techniques vying to satisfy any Goal is additive and may be extended at runtime without needing to modify or remove any existing Techniques. Our system provides a framework in which Techniques may compete and interoperate at runtime in order to maintain an adaptive application. Technique development may be distributed and incremental, providing a path for the decentralized evolution of applications. Benchmarks show that our system imposes reasonable overhead during application startup and adaptation. by Justin Mazzola Paluska. Elec.E. in Computer Science 58 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. Structured decomposition of adaptive applications Thesis application/pdf false Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="0bb5e199-969f-4fd9-bb18-3ed2009477cc"> <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>Structured decomposition of adaptive applications</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2012</PublicationDate> <Authors> <Author> <DisplayName>Paluska, Justin Mazzola, 1981-</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>We describe an approach to automate certain high-level implementation decisions in a pervasive application, allowing them to be postponed until run time. Our system enables a model in which an application programmer can specify the behavior of an adaptive application as a set of open-ended decision points. We formalize decision points as Goals, each of which may be satisfied by a set of scripts called Techniques. The set of Techniques vying to satisfy any Goal is additive and may be extended at runtime without needing to modify or remove any existing Techniques. Our system provides a framework in which Techniques may compete and interoperate at runtime in order to maintain an adaptive application. Technique development may be distributed and incremental, providing a path for the decentralized evolution of applications. Benchmarks show that our system imposes reasonable overhead during application startup and adaptation.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>