Monemizadeh, M., Muthukrishnan, S., Peng, P. orcid.org/0000-0003-2700-5699 et al. (1 more author) (2017) Testable bounded degree graph properties are random order streamable. In: Chatzigiannakis, I., Indyk, P., Kuhn, F. and Muscholl, A., (eds.) 44th International Colloquium on Automata, Languages, and Programming, ICALP 2017. ICALP 2017, 10-14 Jul 2017, Warsaw, Poland. LIPIcs, 80 . Dagstuhl Publishing , Dagstuhl, Germany , 131:1-131:14. ISBN 9783959770415
Abstract
We study which property testing and sublinear time algorithms can be transformed into graph streaming algorithms for random order streams. Our main result is that for bounded degree graphs, any property that is constant-query testable in the adjacency list model can be tested with constant space in a single-pass in random order streams. Our result is obtained by estimating the distribution of local neighborhoods of the vertices on a random order graph stream using constant space. We then show that our approach can also be applied to constant time approximation algorithms for bounded degree graphs in the adjacency list model: As an example, we obtain a constant-space single-pass random order streaming algorithms for approximating the size of a maximum matching with additive error epsilon n (n is the number of nodes). Our result establishes for the first time that a large class of sublinear algorithms can be simulated in random order streams, while Omega(n) space is needed for many graph streaming problems for adversarial orders.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Editors: |
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Copyright, Publisher and Additional Information: | © 2017 The Author(s). This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
Keywords: | Graph streaming algorithms; graph property testing; constant-time approximation algorithms |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 01 Aug 2019 10:30 |
Last Modified: | 01 Aug 2019 10:30 |
Status: | Published |
Publisher: | Dagstuhl Publishing |
Series Name: | LIPIcs |
Refereed: | Yes |
Identification Number: | 10.4230/LIPIcs.ICALP.2017.131 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:148804 |