Improved Deterministic Distributed Maximum Weight Independent Set Approximation in Sparse Graphs

Author Yuval Gil



PDF
Thumbnail PDF

File

LIPIcs.OPODIS.2023.16.pdf
  • Filesize: 0.88 MB
  • 20 pages

Document Identifiers

Author Details

Yuval Gil
  • Technion - Israel Institute of Technology, Haifa, Israel

Acknowledgements

I would like to thank my advisor Yuval Emek for his support. I would also like to thank the anonymous reviewers for their helpful comments.

Cite AsGet BibTex

Yuval Gil. Improved Deterministic Distributed Maximum Weight Independent Set Approximation in Sparse Graphs. In 27th International Conference on Principles of Distributed Systems (OPODIS 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 286, pp. 16:1-16:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)
https://doi.org/10.4230/LIPIcs.OPODIS.2023.16

Abstract

We design new deterministic CONGEST approximation algorithms for maximum weight independent set (MWIS) in sparse graphs. As our main results, we obtain new Δ(1+ε)-approximation algorithms as well as algorithms whose approximation ratio depend strictly on α, in graphs with maximum degree Δ and arboricity α. For (deterministic) Δ(1+ε)-approximation, the current state-of-the-art is due to a recent breakthrough by Faour et al. [SODA 2023] that showed an O(log² (Δ W)⋅ log (1/ε)+log ^{*}n)-round algorithm, where W is the largest node-weight (this bound translates to O(log² n⋅log (1/ε)) under the common assumption that W = poly(n)). As for α-dependent approximations, a deterministic CONGEST (8(1+ε)⋅α)-approximation algorithm with runtime O(log³ n⋅log (1/ε)) can be derived by combining the aforementioned algorithm of Faour et al. with a method presented by Kawarabayashi et al. [DISC 2020]. As our main results, we show the following. - A deterministic CONGEST algorithm that computes an α^{1+τ}-approximation for MWIS in O(log nlog α) rounds for any constant τ > 0. To the best of our knowledge, this is the fastest runtime of any deterministic non-trivial approximation algorithm for MWIS to date. Furthermore, for the large class of graphs where α = Δ^{1-Θ(1)}, it implies a deterministic Δ^{1-Θ(1)}-approximation algorithm with a runtime of O(log nlog α) which improves upon the result of Faour et al. in both approximation ratio (by a Δ^{Θ(1)} factor) and runtime (by an O(log n/log α) factor). - A deterministic CONGEST algorithm that computes an O(α)-approximation for MWIS in O(α^{τ}log n) rounds for any (desirably small) constant τ > 0. This improves the runtime of the best known deterministic O(α)-approximation algorithm in the case that α = O(polylog n). This also leads to a deterministic Δ(1+ε)-approximation algorithm with a runtime of O(α^{τ}log nlog (1/ε)) which improves upon the runtime of Faour et al. in the case that α = O(polylog n). - A deterministic CONGEST algorithm that computes a (⌊(2+ε)α⌋)-approximation for MWIS in O(αlog n) rounds. This improves upon the best known α-dependent approximation ratio by a constant factor. - A deterministic CONGEST algorithm that computes a 2d²-approximation for MWIS in time O(d²+log ^{*}n) in a directed graph with out-degree at most d. The dependency on n is (asymptotically) optimal due to a lower bound by Czygrinow et al. [DISC 2008] and Lenzen and Wattenhofer [DISC 2008]. We note that a key ingredient to all of our algorithms is a novel deterministic method that computes a high-weight subset of nodes whose induced subgraph is sparse.

Subject Classification

ACM Subject Classification
  • Theory of computation → Distributed algorithms
  • Theory of computation → Approximation algorithms analysis
Keywords
  • Approximation algorithms
  • Sparse graphs
  • The CONGEST model

Metrics

  • Access Statistics
  • Total Accesses (updated on a weekly basis)
    0
    PDF Downloads

References

  1. Noga Alon and Nabil Kahalé. Approximating the independence number via the theta-function. Math. Program., 80:253-264, 1998. URL: https://doi.org/10.1007/BF01581168.
  2. Saeed Akhoondian Amiri, Stefan Schmid, and Sebastian Siebertz. A local constant factor MDS approximation for bounded genus graphs. In George Giakkoupis, editor, Proceedings of the 2016 ACM Symposium on Principles of Distributed Computing, PODC 2016, Chicago, IL, USA, July 25-28, 2016, pages 227-233. ACM, 2016. URL: https://doi.org/10.1145/2933057.2933084.
  3. Per Austrin, Subhash Khot, and Muli Safra. Inapproximability of vertex cover and independent set in bounded degree graphs. Theory Comput., 7(1):27-43, 2011. URL: https://doi.org/10.4086/TOC.2011.V007A003.
  4. Nir Bachrach, Keren Censor-Hillel, Michal Dory, Yuval Efron, Dean Leitersdorf, and Ami Paz. Hardness of distributed optimization. In Proceedings of the 2019 ACM Symposium on Principles of Distributed Computing, PODC 2019, Toronto, ON, Canada, July 29 - August 2, 2019, pages 238-247. ACM, 2019. URL: https://doi.org/10.1145/3293611.3331597.
  5. Amotz Bar-Noy, Reuven Bar-Yehuda, Ari Freund, Joseph Naor, and Baruch Schieber. A unified approach to approximating resource allocation and scheduling. J. ACM, 48(5):1069-1090, 2001. URL: https://doi.org/10.1145/502102.502107.
  6. Reuven Bar-Yehuda, Keren Censor-Hillel, Mohsen Ghaffari, and Gregory Schwartzman. Distributed approximation of maximum independent set and maximum matching. In Proceedings of the ACM Symposium on Principles of Distributed Computing, PODC 2017, Washington, DC, USA, July 25-27, 2017, pages 165-174. ACM, 2017. URL: https://doi.org/10.1145/3087801.3087806.
  7. Leonid Barenboim. Deterministic (Δ + 1)-coloring in sublinear (in Δ) time in static, dynamic, and faulty networks. J. ACM, 63(5):47:1-47:22, 2016. URL: https://doi.org/10.1145/2979675.
  8. Leonid Barenboim and Michael Elkin. Deterministic distributed vertex coloring in polylogarithmic time. In Andréa W. Richa and Rachid Guerraoui, editors, Proceedings of the 29th Annual ACM Symposium on Principles of Distributed Computing, PODC 2010, Zurich, Switzerland, July 25-28, 2010, pages 410-419. ACM, 2010. URL: https://doi.org/10.1145/1835698.1835797.
  9. Leonid Barenboim and Michael Elkin. Sublogarithmic distributed MIS algorithm for sparse graphs using nash-williams decomposition. Distributed Comput., 22(5-6):363-379, 2010. URL: https://doi.org/10.1007/S00446-009-0088-2.
  10. Leonid Barenboim, Michael Elkin, and Uri Goldenberg. Locally-iterative distributed (Δ + 1)-coloring and applications. J. ACM, 69(1):5:1-5:26, 2022. URL: https://doi.org/10.1145/3486625.
  11. Keren Censor-Hillel, Seri Khoury, and Ami Paz. Quadratic and near-quadratic lower bounds for the CONGEST model. In 31st International Symposium on Distributed Computing, DISC 2017, October 16-20, 2017, Vienna, Austria, volume 91 of LIPIcs, pages 10:1-10:16. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2017. URL: https://doi.org/10.4230/LIPICS.DISC.2017.10.
  12. Siu On Chan. Approximation resistance from pairwise-independent subgroups. J. ACM, 63(3):27:1-27:32, 2016. URL: https://doi.org/10.1145/2873054.
  13. Yi-Jun Chang and Zeyong Li. The complexity of distributed approximation of packing and covering integer linear programs. CoRR, abs/2305.01324, 2023. URL: https://doi.org/10.48550/ARXIV.2305.01324.
  14. Andrzej Czygrinow, Michal Hanckowiak, and Edyta Szymanska. Fast distributed approximation algorithm for the maximum matching problem in bounded arboricity graphs. In Yingfei Dong, Ding-Zhu Du, and Oscar H. Ibarra, editors, Algorithms and Computation, 20th International Symposium, ISAAC 2009, Honolulu, Hawaii, USA, December 16-18, 2009. Proceedings, volume 5878 of Lecture Notes in Computer Science, pages 668-678. Springer, 2009. URL: https://doi.org/10.1007/978-3-642-10631-6_68.
  15. Andrzej Czygrinow, Michal Hanckowiak, and Wojciech Wawrzyniak. Distributed packing in planar graphs. In Friedhelm Meyer auf der Heide and Nir Shavit, editors, SPAA 2008: Proceedings of the 20th Annual ACM Symposium on Parallelism in Algorithms and Architectures, Munich, Germany, June 14-16, 2008, pages 55-61. ACM, 2008. URL: https://doi.org/10.1145/1378533.1378541.
  16. Andrzej Czygrinow, Michal Hanckowiak, and Wojciech Wawrzyniak. Fast distributed approximations in planar graphs. In Distributed Computing, 22nd International Symposium, DISC 2008, Arcachon, France, September 22-24, 2008. Proceedings, volume 5218, pages 78-92. Springer, 2008. URL: https://doi.org/10.1007/978-3-540-87779-0_6.
  17. Andrzej Czygrinow, Michal Hanckowiak, Wojciech Wawrzyniak, and Marcin Witkowski. Distributed CONGESTBC constant approximation of MDS in bounded genus graphs. Theor. Comput. Sci., 757:1-10, 2019. URL: https://doi.org/10.1016/J.TCS.2018.07.008.
  18. Michal Dory, Mohsen Ghaffari, and Saeed Ilchi. Near-optimal distributed dominating set in bounded arboricity graphs. In Alessia Milani and Philipp Woelfel, editors, PODC '22: ACM Symposium on Principles of Distributed Computing, Salerno, Italy, July 25-29, 2022, pages 292-300. ACM, 2022. URL: https://doi.org/10.1145/3519270.3538437.
  19. Yuval Efron, Ofer Grossman, and Seri Khoury. Beyond alice and bob: Improved inapproximability for maximum independent set in CONGEST. In Yuval Emek and Christian Cachin, editors, PODC '20: ACM Symposium on Principles of Distributed Computing, Virtual Event, Italy, August 3-7, 2020, pages 511-520. ACM, 2020. URL: https://doi.org/10.1145/3382734.3405702.
  20. Salwa Faour, Marc Fuchs, and Fabian Kuhn. Distributed CONGEST approximation of weighted vertex covers and matchings. In Quentin Bramas, Vincent Gramoli, and Alessia Milani, editors, 25th International Conference on Principles of Distributed Systems, OPODIS 2021, December 13-15, 2021, Strasbourg, France, volume 217 of LIPIcs, pages 17:1-17:20. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2021. URL: https://doi.org/10.4230/LIPICS.OPODIS.2021.17.
  21. Salwa Faour, Mohsen Ghaffari, Christoph Grunau, Fabian Kuhn, and Václav Rozhon. Local distributed rounding: Generalized to mis, matching, set cover, and beyond. In Nikhil Bansal and Viswanath Nagarajan, editors, Proceedings of the 2023 ACM-SIAM Symposium on Discrete Algorithms, SODA 2023, Florence, Italy, January 22-25, 2023, pages 4409-4447. SIAM, 2023. URL: https://doi.org/10.1137/1.9781611977554.CH168.
  22. Uriel Feige. Approximating maximum clique by removing subgraphs. SIAM J. Discret. Math., 18(2):219-225, 2004. URL: https://doi.org/10.1137/S089548010240415X.
  23. Mohsen Ghaffari, Fabian Kuhn, and Yannic Maus. On the complexity of local distributed graph problems. In Hamed Hatami, Pierre McKenzie, and Valerie King, editors, Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing, STOC 2017, Montreal, QC, Canada, June 19-23, 2017, pages 784-797. ACM, 2017. URL: https://doi.org/10.1145/3055399.3055471.
  24. Andrew V. Goldberg, Serge A. Plotkin, and Gregory E. Shannon. Parallel symmetry-breaking in sparse graphs. SIAM J. Discret. Math., 1(4):434-446, 1988. URL: https://doi.org/10.1137/0401044.
  25. Magnús M. Halldórsson. Approximations of independent sets in graphs. In Klaus Jansen and Dorit S. Hochbaum, editors, Approximation Algorithms for Combinatorial Optimization, International Workshop APPROX'98, Aalborg, Denmark, July 18-19, 1998, Proceedings, volume 1444 of Lecture Notes in Computer Science, pages 1-13. Springer, 1998. URL: https://doi.org/10.1007/BFB0053959.
  26. Magnús M. Halldórsson. Approximations of weighted independent set and hereditary subset problems. J. Graph Algorithms Appl., 4(1):1-16, 2000. URL: https://doi.org/10.7155/JGAA.00020.
  27. Eran Halperin. Improved approximation algorithms for the vertex cover problem in graphs and hypergraphs. SIAM J. Comput., 31(5):1608-1623, 2002. URL: https://doi.org/10.1137/S0097539700381097.
  28. Johan Håstad. Clique is hard to approximate within n^1-epsilon. In 37th Annual Symposium on Foundations of Computer Science, FOCS '96, Burlington, Vermont, USA, 14-16 October, 1996, pages 627-636. IEEE Computer Society, 1996. Google Scholar
  29. David R. Karger, Rajeev Motwani, and Madhu Sudan. Approximate graph coloring by semidefinite programming. J. ACM, 45(2):246-265, 1998. URL: https://doi.org/10.1145/274787.274791.
  30. Richard M. Karp. Reducibility among combinatorial problems. In Proceedings of a symposium on the Complexity of Computer Computations, held March 20-22, 1972, at the IBM Thomas J. Watson Research Center, Yorktown Heights, New York, USA, The IBM Research Symposia Series, pages 85-103. Plenum Press, New York, 1972. URL: https://doi.org/10.1007/978-1-4684-2001-2_9.
  31. Ken-ichi Kawarabayashi, Seri Khoury, Aaron Schild, and Gregory Schwartzman. Improved distributed approximations for maximum independent set. In 34th International Symposium on Distributed Computing, DISC 2020, October 12-16, 2020, Virtual Conference, volume 179, pages 35:1-35:16. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2020. URL: https://doi.org/10.4230/LIPICS.DISC.2020.35.
  32. Christoph Lenzen and Roger Wattenhofer. Leveraging linial’s locality limit. In Distributed Computing, 22nd International Symposium, DISC 2008, Arcachon, France, September 22-24, 2008. Proceedings, volume 5218 of Lecture Notes in Computer Science, pages 394-407. Springer, 2008. URL: https://doi.org/10.1007/978-3-540-87779-0_27.
  33. Christoph Lenzen and Roger Wattenhofer. Minimum dominating set approximation in graphs of bounded arboricity. In Nancy A. Lynch and Alexander A. Shvartsman, editors, Distributed Computing, 24th International Symposium, DISC 2010, Cambridge, MA, USA, September 13-15, 2010. Proceedings, volume 6343 of Lecture Notes in Computer Science, pages 510-524. Springer, 2010. URL: https://doi.org/10.1007/978-3-642-15763-9_48.
  34. Nathan Linial. Locality in distributed graph algorithms. SIAM J. Comput., 21(1):193-201, 1992. URL: https://doi.org/10.1137/0221015.
  35. Adir Morgan, Shay Solomon, and Nicole Wein. Algorithms for the minimum dominating set problem in bounded arboricity graphs: Simpler, faster, and combinatorial. In Seth Gilbert, editor, 35th International Symposium on Distributed Computing, DISC 2021, October 4-8, 2021, Freiburg, Germany (Virtual Conference), volume 209 of LIPIcs, pages 33:1-33:19. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2021. URL: https://doi.org/10.4230/LIPICS.DISC.2021.33.
  36. David Peleg. Distributed Computing: A Locality-Sensitive Approach. Society for Industrial and Applied Mathematics, 2000. URL: https://doi.org/10.1137/1.9780898719772.
  37. Václav Rozhon and Mohsen Ghaffari. Polylogarithmic-time deterministic network decomposition and distributed derandomization. In Proccedings of the 52nd Annual ACM SIGACT Symposium on Theory of Computing, STOC 2020, Chicago, IL, USA, June 22-26, 2020, pages 350-363. ACM, 2020. URL: https://doi.org/10.1145/3357713.3384298.
  38. Vijay V. Vazirani. Approximation algorithms. Springer, 2001. URL: http://www.springer.com/computer/theoretical+computer+science/book/978-3-540-65367-7.
Questions / Remarks / Feedback
X

Feedback for Dagstuhl Publishing


Thanks for your feedback!

Feedback submitted

Could not send message

Please try again later or send an E-mail