dc.contributor.advisor | Virginia V. Williams. | en_US |
dc.contributor.author | Lu, Kevin(Kevin Z.) | en_US |
dc.contributor.other | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. | en_US |
dc.date.accessioned | 2019-12-05T18:06:31Z | |
dc.date.available | 2019-12-05T18:06:31Z | |
dc.date.copyright | 2019 | en_US |
dc.date.issued | 2019 | en_US |
dc.identifier.uri | https://hdl.handle.net/1721.1/123156 | |
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 | Thesis: M. Eng. in Computer Science and Engineering, Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2019 | en_US |
dc.description | Cataloged from student-submitted PDF version of thesis. | en_US |
dc.description | Includes bibliographical references (pages 47-49). | en_US |
dc.description.abstract | A 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.statementofresponsibility | by Kevin Lu. | en_US |
dc.format.extent | 49 pages | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Massachusetts Institute of Technology | en_US |
dc.rights | MIT 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.uri | http://dspace.mit.edu/handle/1721.1/7582 | en_US |
dc.subject | Electrical Engineering and Computer Science. | en_US |
dc.title | New methods for approximating shortest paths | en_US |
dc.type | Thesis | en_US |
dc.description.degree | M. Eng. in Computer Science and Engineering | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science | en_US |
dc.identifier.oclc | 1128882854 | en_US |
dc.description.collection | M.Eng.inComputerScienceandEngineering Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science | en_US |
dspace.imported | 2019-12-05T18:06:30Z | en_US |
mit.thesis.degree | Master | en_US |
mit.thesis.department | EECS | en_US |