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Efficient algorithms for new computational models

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dc.contributor.advisor David R. Karger. en_US Ruhl, Jan Matthias, 1973- en_US
dc.contributor.other Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. en_US 2005-05-19T15:40:48Z 2005-05-19T15:40:48Z 2003 en_US 2003 en_US
dc.description Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2003. en_US
dc.description Includes bibliographical references (p. 155-163). en_US
dc.description This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. en_US
dc.description.abstract Advances in hardware design and manufacturing often lead to new ways in which problems can be solved computationally. In this thesis we explore fundamental problems in three computational models that are based on such recent advances. The first model is based on new chip architectures, where multiple independent processing units are placed on one chip, allowing for an unprecedented parallelism in hardware. We provide new scheduling algorithms for this computational model. The second model is motivated by peer-to-peer networks, where countless (often inexpensive) computing devices cooperate in distributed applications without any central control. We state and analyze new algorithms for load balancing and for locality-aware distributed data storage in peer-to-peer networks. The last model is based on extensions of the streaming model. It is an attempt to capture the class of problems that can be efficiently solved on massive data sets. We give a number of algorithms for this model, and compare it to other models that have been proposed for massive data set computations. Our algorithms and complexity results for these computational models follow the central thesis that it is an important part of theoretical computer science to model real-world computational structures, and that such effort is richly rewarded by a plethora of interesting and challenging problems. en_US
dc.description.statementofresponsibility by Jan Matthias Ruhl. en_US
dc.format.extent 163 p. en_US
dc.format.extent 1188364 bytes
dc.format.extent 1287306 bytes
dc.format.mimetype application/pdf
dc.format.mimetype application/pdf
dc.language.iso eng en_US
dc.publisher Massachusetts Institute of Technology en_US
dc.rights 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. en_US
dc.subject Electrical Engineering and Computer Science. en_US
dc.title Efficient algorithms for new computational models en_US
dc.type Thesis en_US Ph.D. en_US
dc.contributor.department Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. en_US
dc.identifier.oclc 54457280 en_US

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