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Better Distance Preservers and Additive Spanners

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sword-2022-07-21T17:03:31.original.xml (130 B)
Original SWORD entry document
Author(s)
Bodwin, Greg
•
Williams, Virginia Vassilevska
Date Issued
2021
Journal
ACM Transactions on Algorithms
Publisher
Association for Computing Machinery (ACM)
Citation
Bodwin, Greg and Williams, Virginia Vassilevska. 2021. "Better Distance Preservers and Additive Spanners." ACM Transactions on Algorithms, 17 (4).
Version
Author's final manuscript
Abstract

We study two popular ways to sketch the shortest path distances of an input graph. The first is distance preservers , which are sparse subgraphs that agree with the distances of the original graph on a given set of demand pairs. Prior work on distance preservers has exploited only a simple structural property of shortest paths, called consistency , stating that one can break shortest path ties such that no two paths intersect, split apart, and then intersect again later. We prove that consistency alone is not enough to understand distance preservers, by showing both a lower bound on the power of consistency and a new general upper bound that polynomially surpasses it. Specifically, our new upper bound is that any p demand pairs in an n -node undirected unweighted graph have a distance preserver on O( n 2/3 p 2/3 + np 1/3 edges. We leave a conjecture that the right bound is O ( n 2/3 p 2/3 + n ) or better. The second part of this paper leverages these distance preservers in a new construction of additive spanners , which are subgraphs that preserve all pairwise distances up to an additive error function. We give improved error bounds for spanners with relatively few edges; for example, we prove that all graphs have spanners on O(n) edges with + O ( n 3/7 + ε ) error. Our construction can be viewed as an extension of the popular path-buying framework to clusters of larger radii.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
http://creativecommons.org/licenses/by-nc-sa/4.0/
Persistent DSpace Link
https://hdl.handle.net/1721.1/143945
DOI of Published Version
https://doi.org/10.1145/3490147
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