skip to main content
research-article
Public Access

Tight Lower Bounds on Graph Embedding Problems

Authors Info & Claims
Published:16 June 2017Publication History
Skip Abstract Section

Abstract

We prove that unless the Exponential Time Hypothesis (ETH) fails, deciding if there is a homomorphism from graph G to graph H cannot be done in time |V(H)|o(|V(G)|). We also show an exponential-time reduction from Graph Homomorphism to Subgraph Isomorphism. This rules out (subject to ETH) a possibility of |V(H)|o(|V(H)|)-time algorithm deciding if graph G is a subgraph of H. For both problems our lower bounds asymptotically match the running time of brute-force algorithms trying all possible mappings of one graph into another. Thus, our work closes the gap in the known complexity of these fundamental problems.

Moreover, as a consequence of our reductions, conditional lower bounds follow for other related problems such as Locally Injective Homomorphism, Graph Minors, Topological Graph Minors, Minimum Distortion Embedding and Quadratic Assignment Problem.

References

  1. Omid Amini, Fedor V. Fomin, and Saket Saurabh. 2012. Counting subgraphs via homomorphisms. SIAM J. Discr. Math. 26, 2 (2012), 695--717.Google ScholarGoogle ScholarCross RefCross Ref
  2. Per Austrin. 2010. Towards sharp inapproximability for any 2-CSP. SIAM J. Comput. 39, 6 (2010), 2430--2463.Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Mihai Bădoiu, Julia Chuzhoy, Piotr Indyk, and Anastasios Sidiropoulos. 2005a. Low-distortion embeddings of general metrics into the line. In Proceedings of the 37th Annual ACM Symposium on Theory of Computing (STOC’05). ACM, 225--233. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Mihai Bădoiu, Kedar Dhamdhere, Anupam Gupta, Yuri Rabinovich, Harald Räcke, R. Ravi, and Anastasios Sidiropoulos. 2005b. Approximation algorithms for low-distortion embeddings into low-dimensional spaces. In Proceedings of the 16th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA’05). SIAM, 119--128. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Libor Barto, Marcin Kozik, and Todd Niven. 2008. Graphs, polymorphisms and the complexity of homomorphism problems. In Proceedings of the 40th Annual ACM Symposium on Theory of Computing (STOC’08). 789--796. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Richard Beigel and David Eppstein. 2005. 3-coloring in time O(1.3289<sup>n</sup>). J. Algor. 54, 2 (2005), 444--453. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Andreas Björklund. 2014. Determinant sums for undirected hamiltonicity. SIAM J. Comput. 43, 1 (2014), 280--299.Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Andreas Björklund, Thore Husfeldt, and Mikko Koivisto. 2009. Set partitioning via inclusion--exclusion. SIAM J. Comput. 39, 2 (2009), 546--563. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Nicolas Bourgeois, Bruno Escoffier, Vangelis Th. Paschos, and Johan M. M. van Rooij. 2012. Fast algorithms for max independent set. Algorithmica 62, 1--2 (2012), 382--415. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Jianer Chen, Xiuzhen Huang, Iyad A. Kanj, and Ge Xia. 2006. Strong computational lower bounds via parameterized complexity. J. Comput. Syst. Sci. 72, 8 (2006), 1346--1367. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Marek Cygan, Fedor Fomin, Bart M. P. Jansen, Łukasz Kowalik, Daniel Lokshtanov, Dániel Marx, Marcin Pilipczuk, Michał Pilipczuk, and Saket Saurabh. 2014. School on Parameterized Algorithms and Complexity—Open Problems. Retrieved from http://fptschool.mimuw.edu.pl/opl.pdf.Google ScholarGoogle Scholar
  12. Marek Cygan, Fedor V. Fomin, Łukasz Kowalik, Dániel Lokshtanov, Daniel Marx, Marcin Pilipczuk, Michał Pilipczuk, and Saket Saurabh. 2015. Parameterized Algorithms. Springer. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Marek Cygan and Marcin Pilipczuk. 2012. Bandwidth and distortion revisited. Discr. Appl. Math. 160, 4--5 (2012), 494--504.Google ScholarGoogle ScholarCross RefCross Ref
  14. Tomás Feder and Moshe Y. Vardi. 1998. The computational structure of monotone monadic SNP and constraint satisfaction: A study through datalog and group theory. SIAM J. Comput. 28, 1 (1998), 57--104. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Uriel Feige. 2000. Coping with the NP-hardness of the graph bandwidth problem. In Proceedings of the 7th Scandinavian Workshop on Algorithm Theory (SWAT’00). Lecture Notes in Computer Science, Vol. 1851. Springer, Berlin, 10--19. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Michael R. Fellows, Fedor V. Fomin, Daniel Lokshtanov, Elena Losievskaja, Frances A. Rosamond, and Saket Saurabh. 2013. Distortion is fixed parameter tractable. ACM Trans. Comput. Theory 5, 4 (2013), 16. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Jirí Fiala, Petr A. Golovach, and Jan Kratochvíl. 2008. Computational complexity of the distance constrained labeling problem for trees (extended abstract). In Proceedings of the 35th International Colloquium of Automata, Languages and Programming (ICALP’08). Lecture Notes in Computer Science, Vol. 5125. Springer, 294--305. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Jirí Fiala and Jan Kratochvíl. 2008. Locally constrained graph homomorphisms - structure, complexity, and applications. Comput. Sci. Rev. 2, 2 (2008), 97--111. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Fedor Fomin, Kazuo Iwama, and Dieter Kratsch. 2008. Moderately exponential time algorithms (dagstuhl seminar 08431). In Dagstuhl Reports. Retrieved from http://drops.dagstuhl.de/opus/volltexte/2008/1798/pdf/08431.SWM.Paper.1798.pdf. 1.Google ScholarGoogle Scholar
  20. Fedor V. Fomin, Pinar Heggernes, and Dieter Kratsch. 2007. Exact algorithms for graph homomorphisms. Theor. Comput. Syst. 41, 2 (2007), 381--393. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Fedor V. Fomin and Dieter Kratsch. 2010. Exact Exponential Algorithms. Springer. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Fedor V. Fomin, Daniel Lokshtanov, and Saket Saurabh. 2011. An exact algorithm for minimum distortion embedding. Theor. Comput. Sci. 412, 29 (2011), 3530--3536. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Michael R. Garey and David S. Johnson. 1979. Computers and Intractability: A Guide to the Theory of NP-Completeness. W. H. Freeman. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Jerrold R. Griggs and Roger K. Yeh. 1992. Labelling Graphs with a Condition at Distance 2. SIAM J. Discr. Math. 5, 4 (1992), 586--595. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Martin Grohe. 2007. The complexity of homomorphism and constraint satisfaction problems seen from the other side. J. ACM 54, 1 (2007). Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. Frédéric Havet, Martin Klazar, Jan Kratochvíl, Dieter Kratsch, and Mathieu Liedloff. 2011. Exact algorithms for L(2, 1)-labeling of graphs. Algorithmica 59, 2 (2011), 169--194. Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. Michael Held and Richard M. Karp. 1962. A dynamic programming approach to sequencing problems. J. SIAM 10 (1962), 196--210.Google ScholarGoogle Scholar
  28. Pavol Hell and Jaroslav Nešetřil. 1990. On the complexity of H-coloring. J. Combin. Theory Ser. B 48, 1 (1990), 92--110. Google ScholarGoogle ScholarDigital LibraryDigital Library
  29. Pavol Hell and Jaroslav Nešetřil. 2004. Graphs and Homomorphisms. Oxford Lecture Series in Mathematics and its Applications, Vol. 28. Oxford University Press, Oxford.Google ScholarGoogle Scholar
  30. Thore Husfeldt, Ramamohan Paturi, Gregory B. Sorkin, and Ryan Williams. 2013. Exponential algorithms: Algorithms and complexity beyond polynomial time (dagstuhl seminar 13331). In Dagstuhl Reports. Retrieved from http://drops.dagstuhl.de/opus/volltexte/2013/4342/pdf/dagrep_v003_i008_p040_s13331.pdf. 63.Google ScholarGoogle Scholar
  31. Russell Impagliazzo and Ramamohan Paturi. 2001. On the complexity of k-SAT. J. Comput. Syst. Sci. 62, 2 (2001), 367--375. Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. Russell Impagliazzo, Ramamohan Paturi, and Francis Zane. 2001a. Which problems have strongly exponential complexity? J. Comput. Syst. Sci. 63, 4 (2001), 512--530. Google ScholarGoogle ScholarDigital LibraryDigital Library
  33. Russell Impagliazzo, Ramamohan Paturi, and Francis Zane. 2001b. Which problems have strongly exponential complexity. J. Comput. Syst. Sci. 63, 4 (2001), 512--530. Google ScholarGoogle ScholarDigital LibraryDigital Library
  34. Konstanty Junosza-Szaniawski, Jan Kratochvíl, Mathieu Liedloff, Peter Rossmanith, and Paweł Rzażewski. 2013. Fast exact algorithm for L(2, 1)-labeling of graphs. Theor. Comput. Sci. 505 (2013), 42--54. Google ScholarGoogle ScholarDigital LibraryDigital Library
  35. Claire Kenyon, Yuval Rabani, and Alistair Sinclair. 2009. Low distortion maps between point sets. SIAM J. Comput. 39, 4 (2009), 1617--1636.Google ScholarGoogle ScholarDigital LibraryDigital Library
  36. Eugene L. Lawler. 1976. A note on the complexity of the chromatic number problem. Inf. Process. Lett. 5, 3 (1976), 66--67.Google ScholarGoogle ScholarCross RefCross Ref
  37. Andrzej Lingas and Martin Wahlen. 2009. An exact algorithm for subgraph homeomorphism. J. Discr. Algorithms 7, 4 (2009), 464--468. Google ScholarGoogle ScholarDigital LibraryDigital Library
  38. Daniel Lokshtanov, Dániel Marx, and Saket Saurabh. 2011. Lower bounds based on the exponential time hypothesis. Bull. EATCS 105 (2011), 41--72.Google ScholarGoogle Scholar
  39. Daniel Lokshtanov, Dániel Marx, and Saket Saurabh. 2013. Lower bounds based on the exponential time hypothesis. Bull. EATCS 3, 105 (2013).Google ScholarGoogle Scholar
  40. László Lovász. 2012. Large Networks and Graph Limits. Vol. 60. American Mathematical Soc.Google ScholarGoogle Scholar
  41. Dániel Marx. 2010. Can you beat treewidth? Theor. Comput. 6, 1 (2010), 85--112.Google ScholarGoogle ScholarCross RefCross Ref
  42. Dániel Marx and Michal Pilipczuk. 2014. Everything you always wanted to know about the parameterized complexity of Subgraph Isomorphism (but were afraid to ask). In Proceedings of the 31st International Symposium on Theoretical Aspects of Computer Science (STACS’14). 542--553.Google ScholarGoogle Scholar
  43. Prasad Raghavendra. 2008. Optimal algorithms and inapproximability results for every CSP? In Proceedings of the 40th Annual ACM Symposium on Theory of Computing (STOC’08). 245--254. Google ScholarGoogle ScholarDigital LibraryDigital Library
  44. Neil Robertson and Paul D. Seymour. 1995. Graph minors. XIII. The disjoint paths problem. J. Combin. Theory Ser. B 63, 1 (1995), 65--110. Google ScholarGoogle ScholarDigital LibraryDigital Library
  45. J. M. Robson. 1986. Algorithms for maximum independent sets. J. Algor. 7, 3 (1986), 425--440.Google ScholarGoogle ScholarCross RefCross Ref
  46. Paweł Rzażewski. 2014. Exact algorithm for graph homomorphism and locally injective graph homomorphism. Inf. Process. Lett. 114, 7 (2014), 387--391. Google ScholarGoogle ScholarDigital LibraryDigital Library
  47. Michael Sipser. 2005. Introduction to the Theory of Computation. Cengage Learning.Google ScholarGoogle Scholar
  48. Robert Endre Tarjan and Anthony E. Trojanowski. 1977. Finding a maximum independent set. SIAM J. Comput. 6, 3 (1977), 537--546.Google ScholarGoogle ScholarDigital LibraryDigital Library
  49. Patrick Traxler. 2008. The time complexity of constraint satisfaction. In Parameterized and Exact Computation. Springer, 190--201. Google ScholarGoogle ScholarDigital LibraryDigital Library
  50. Magnus Wahlström. 2010. Problem 5.21. time complexity of graph homomorphism. In Exact Complexity of NP-Hard Problems. Dagstuhl Seminar 10441 Final Report, Ramamohan Paturi Thore Husfeldt, Dieter Kratsch and Gregory Sorkin (Eds.). Dagstuhl.Google ScholarGoogle Scholar
  51. Magnus Wahlström. 2011. New plain-exponential time classes for graph homomorphism. Theor. Comput. Syst. 49, 2 (2011), 273--282. Google ScholarGoogle ScholarDigital LibraryDigital Library
  52. Gerhard J. Woeginger. 2003. Exact algorithms for NP-hard problems: A survey. In Combinatorial Optimization—Eureka, You Shrink&excl;Lecture Notes in Computer Science, Vol. 2570. Springer-Verlag, Berlin, 185--207. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Tight Lower Bounds on Graph Embedding Problems

      Recommendations

      Comments

      Login options

      Check if you have access through your login credentials or your institution to get full access on this article.

      Sign in

      Full Access

      • Published in

        cover image Journal of the ACM
        Journal of the ACM  Volume 64, Issue 3
        June 2017
        294 pages
        ISSN:0004-5411
        EISSN:1557-735X
        DOI:10.1145/3107927
        Issue’s Table of Contents

        Copyright © 2017 ACM

        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 16 June 2017
        • Accepted: 1 February 2017
        • Revised: 1 October 2016
        • Received: 1 February 2016
        Published in jacm Volume 64, Issue 3

        Permissions

        Request permissions about this article.

        Request Permissions

        Check for updates

        Qualifiers

        • research-article
        • Research
        • Refereed

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader