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Fast Distributed Approximation Algorithm for the Maximum Matching Problem in Bounded Arboricity Graphs

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Algorithms and Computation (ISAAC 2009)

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Abstract

We give a deterministic distributed approximation algorithm for the maximum matching problem in graphs of bounded arboricity. Specifically, given 0 < ε< 1 and a positive integer a, the algorithm finds a matching of size at least (1 − ε)m(G), where m(G) is the size of the maximum matching in an n-vertex graph G with arboricity at most a. The algorithm runs in O(log* n) rounds in the message passing model and it is the first sublogarithmic algorithm for the problem on such a wide class of graphs. Moreover, the result implies that the known \(\Omega(\sqrt{\log n/\log\log n})\) lower bound on the time complexity for a constant or polylogarithmic approximation does not hold for graphs of bounded arboricity.

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References

  1. Barenboim, L., Elkin, M.: Sublogarithmic distributed MIS algorithm for sparse graphs using Nash-Williams decomposition. In: PODC 2008, pp. 25–34 (2008)

    Google Scholar 

  2. Cole, R., Vishkin, U.: Deterministic coin tossing with applications to optimal parallel list ranking. Information and Control 70, 32–53 (1986)

    Article  MATH  MathSciNet  Google Scholar 

  3. Czygrinow, A., Hańćkowiak, M.: Distributed Algorithm for Better Approximation of the Maximum Matching. In: Warnow, T.J., Zhu, B. (eds.) COCOON 2003. LNCS, vol. 2697, pp. 242–251. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  4. Czygrinow, A., Hańćkowiak, M.: Distributed approximation algorithms in unit-disc graphs. In: Dolev, S. (ed.) DISC 2006. LNCS, vol. 4167, pp. 385–398. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  5. Czygrinow, A., Hańćkowiak, M., Szymańska, E.: Distributed algorithm for approximating the maximum matching. Discrete Applied Math. 143(1-3), 62–71 (2004)

    Article  MATH  Google Scholar 

  6. Czygrinow, A., Hańćkowiak, M., Szymańska, E.: Distributed Approximation Algorithms for Planar Graphs. In: Calamoneri, T., Finocchi, I., Italiano, G.F. (eds.) CIAC 2006. LNCS, vol. 3998, pp. 296–307. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

  7. Czygrinow, A., Hańćkowiak, M., Wawrzyniak, W.: Fast distributed approximations in planar graphs. In: Taubenfeld, G. (ed.) DISC 2008. LNCS, vol. 5218, pp. 78–92. Springer, Heidelberg (2008)

    Chapter  Google Scholar 

  8. Diestel, R.: Graph Theory, 3rd edn. Springer, Heidelberg (2005)

    MATH  Google Scholar 

  9. Elkin, M.: An Overview of Distributed Approximation. ACM SIGACT News Distributed Computing Column 35(4-132), 40–57 (2004)

    Article  Google Scholar 

  10. Hańćkowiak, M., Karoński, M., Panconesi, A.: On the distributed complexity of computing maximal matchings. SIAM J. Discrete Math. 15(1), 41–57 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  11. Hopcroft, A., Karp, R.: An n 5/2 algorithm for maximum matching in bipartite graphs. SIAM J. on Comp. 2, 225–231 (1973)

    Article  MATH  MathSciNet  Google Scholar 

  12. Israeli, A., Itai, A.: A fast and simple randomized parallel algorithm for maximal matching. Info. Proc. Lett. 22(2), 77–80 (1986)

    Article  MathSciNet  Google Scholar 

  13. Kuhn, F., Moscibroda, T., Wattenhofer, R.: What Cannot Be Computed Locally! In: Proc. PODC, pp. 300–309 (2004)

    Google Scholar 

  14. Kuhn, F., Moscibroda, T., Nieberg, T., Wattenhofer, R.: Fast Deterministic Distributed Maximal Independent Set Computation on Growth-Bounded Graphs. In: Fraigniaud, P. (ed.) DISC 2005. LNCS, vol. 3724, pp. 273–287. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  15. Kuhn, F., Moscibroda, T., Nieberg, T., Wattenhofer, R.: Local Approximation Schemes for Ad Hoc and Sensor Networks. In: 3rd ACM Joint Workshop on Foundations of Mobile Computing (DIALM-POMC), pp. 97–103 (2005)

    Google Scholar 

  16. Kuhn, F., Moscibroda, T., Wattenhofer, R.: The price of being near-sighted. In: Proc. SODA, pp. 980–989 (2005)

    Google Scholar 

  17. Lotker, Z., Patt-Shamir, B., Pettie, S.: Improved distributed approximate matching. In: SPAA 2008, pp. 129–136 (2008)

    Google Scholar 

  18. Panconesi, A., Rizzi, R.: Some simple distributed algorithms for sparse networks. Distributed Computing 14(2), 97–100 (2001)

    Article  Google Scholar 

  19. Peleg, D.: Distributed Algorithms, A Locality-Sensitive Approach. SIAM Press, Philadelphia (2000)

    Google Scholar 

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Czygrinow, A., Hańćkowiak, M., Szymańska, E. (2009). Fast Distributed Approximation Algorithm for the Maximum Matching Problem in Bounded Arboricity Graphs. In: Dong, Y., Du, DZ., Ibarra, O. (eds) Algorithms and Computation. ISAAC 2009. Lecture Notes in Computer Science, vol 5878. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10631-6_68

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  • DOI: https://doi.org/10.1007/978-3-642-10631-6_68

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-10630-9

  • Online ISBN: 978-3-642-10631-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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