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Linear Programming in the Semi-streaming Model with Application to the Maximum Matching Problem

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Automata, Languages and Programming (ICALP 2011)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6756))

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Abstract

In this paper, we study linear programming based approaches to the maximum matching problem in the semi-streaming model. The semi-streaming model has gained attention as a model for processing massive graphs as the importance of such graphs has increased. This is a model where edges are streamed-in in an adversarial order and we are allowed a space proportional to the number of vertices in a graph.

In recent years, there has been several new results in this semi-streaming model. However broad techniques such as linear programming have not been adapted to this model. We present several techniques to adapt and optimize linear programming based approaches in the semi-streaming model with an application to the maximum matching problem. As a consequence, we improve (almost) all previous results on this problem, and also prove new results on interesting variants.

Research supported in part by an NSF Award CCF-0644119, IIS-0713267 and a gift from Google.

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Authors and Affiliations

  1. Department of Computer Information Sciences, University of Pennsylvania, PA, 19104, USA

    Kook Jin Ahn & Sudipto Guha

Authors
  1. Kook Jin Ahn
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  2. Sudipto Guha
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Editors and Affiliations

  1. ICE-TCS, School of Computer Science, Reykjavik University, Menntavegur 1, IS 101, Reykjavik, Iceland

    Luca Aceto

  2. Fakultät für Informatik, Universität Wien, Universitätsstraße10/9, 1090, Wien, Österreich, Austria

    Monika Henzinger

  3. Department of Applied Mathematics, Charles University, Malostranské nám. 25, 118 00, Praha 1, Czech Republic

    Jiří Sgall

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Ahn, K.J., Guha, S. (2011). Linear Programming in the Semi-streaming Model with Application to the Maximum Matching Problem. In: Aceto, L., Henzinger, M., Sgall, J. (eds) Automata, Languages and Programming. ICALP 2011. Lecture Notes in Computer Science, vol 6756. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22012-8_42

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  • DOI: https://doi.org/10.1007/978-3-642-22012-8_42

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-22011-1

  • Online ISBN: 978-3-642-22012-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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