Efficient algorithms for new computational models
Name
54457280-MIT.pdf
Description
Full printable version
Size
1.23 MB
Format
Adobe PDF
Checksum (MD5)
193259bc218776bc027b96947d2b62ee
Author(s)
Ruhl, Jan Matthias, 1973-
Advisor(s)
David R. Karger.
Date Issued
2003
Publisher
Massachusetts Institute of Technology
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.
Description
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2003.
Includes bibliographical references (p. 155-163).
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Subjects
Electrical Engineering and Computer Science.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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