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Structured decomposition of adaptive applications

Author(s)
Paluska, Justin Mazzola, 1981-
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Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Advisor
Steve Ward.
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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
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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.
Description
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).
 
Date issued
2012
URI
http://hdl.handle.net/1721.1/71275
Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Publisher
Massachusetts Institute of Technology
Keywords
Electrical Engineering and Computer Science.

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