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dc.contributor.advisorVirginia V. Williams.en_US
dc.contributor.authorLu, Kevin(Kevin Z.)en_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.en_US
dc.date.accessioned2019-12-05T18:06:31Z
dc.date.available2019-12-05T18:06:31Z
dc.date.copyright2019en_US
dc.date.issued2019en_US
dc.identifier.urihttps://hdl.handle.net/1721.1/123156
dc.descriptionThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.en_US
dc.descriptionThesis: M. Eng. in Computer Science and Engineering, Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2019en_US
dc.descriptionCataloged from student-submitted PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 47-49).en_US
dc.description.abstractA spanner H of a graph G is a sparse subgraph that approximates all pairwise distances. Of particular interest are additive spanners on unweighted graphs, which satisfy the following for and two vertices u, v. dist(H, u, v) a L d dist(G, u, v) + f(n), where dist is the distance with respect to the graph H or G and f(n) is a function of the number of vertices of the graph. We study a variety of problems related to additive spanners, and have two new results of significance. For additive spanners with O (n) edges, it is well known that f(n) must be a polynomial function O(n[alpha]) for some 0 < [alpha] < 1. Previously, it was known that the optimal value of [alpha was between 1/13 and 3/7; by combining two previously known methods, our first significant result improves the lower bound from 1/13 to 1/11. The all pairs approximate shortest paths problem takes as input an unweighted graph, and outputs a distance matrix that approximates all pairwise distances. We present a new improvement to the algorithm of Dor, Halperin, and Zwick for the +4 and +6 approximation algorithms. In the +4 approximation algorithm, our new algorithm runs in O(n 15/7) time, an improvement from the previous O(n 11/5), and in the +6 approximation algorithm, out new algorithm runs in O(n 9/9) time, an improvement from the previous O(n 17/8).en_US
dc.description.statementofresponsibilityby Kevin Lu.en_US
dc.format.extent49 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectElectrical Engineering and Computer Science.en_US
dc.titleNew methods for approximating shortest pathsen_US
dc.typeThesisen_US
dc.description.degreeM. Eng. in Computer Science and Engineeringen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.identifier.oclc1128882854en_US
dc.description.collectionM.Eng.inComputerScienceandEngineering Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Scienceen_US
dspace.imported2019-12-05T18:06:30Zen_US
mit.thesis.degreeMasteren_US
mit.thesis.departmentEECSen_US


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