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Constrained and Ordered Level Planarity Parameterized by the Number of Levels (2403.13702v2)

Published 20 Mar 2024 in cs.CG

Abstract: The problem Level Planarity asks for a crossing-free drawing of a graph in the plane such that vertices are placed at prescribed y-coordinates (called levels) and such that every edge is realized as a y-monotone curve. In the variant Constrained Level Planarity (CLP), each level $y$ is equipped with a partial order $\prec_y$ on its vertices and in the desired drawing the left-to-right order of vertices on level $y$ has to be a linear extension of $\prec_y$. Ordered Level Planarity (OLP) corresponds to the special case of CLP where the given partial orders $\prec_y$ are total orders. Previous results by Br\"uckner and Rutter [SODA 2017] and Klemz and Rote [ACM Trans. Alg. 2019] state that both CLP and OLP are NP-hard even in severely restricted cases. In particular, they remain NP-hard even when restricted to instances whose width (the maximum number of vertices that may share a common level) is at most two. In this paper, we focus on the other dimension: we study the parameterized complexity of CLP and OLP with respect to the height (the number of levels). We show that OLP parameterized by the height is complete with respect to the complexity class XNLP, which was first studied by Elberfeld et al. Algorithmica 2015 and recently made more prominent by Bodlaender et al. [FOCS 2021]. It contains all parameterized problems that can be solved nondeterministically in time $f(k) n{O(1)}$ and space $f(k) \log n$ (where $f$ is a computable function, $n$ is the input size, and $k$ is the parameter). If a problem is XNLP-complete, it lies in XP, but is W[$t$]-hard for every $t$. In contrast to the fact that OLP parameterized by the height lies in XP, it turns out that CLP is NP-hard even when restricted to instances of height 4. We complement this result by showing that CLP can be solved in polynomial time for instances of height at most 3.

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References (28)
  1. The importance of being proper: (in clustered-level planarity and T𝑇Titalic_T-level planarity). Theor. Comput. Sci., 571:1–9, 2015. Conference version in Proc. GD 2014 (doi:10.1007/978-3-662-45803-7_21). doi:10.1016/j.tcs.2014.12.019.
  2. Beyond level planarity: Cyclic, torus, and simultaneous level planarity. Theor. Comput. Sci., 804:161–170, 2020. Conference version in Proc. GD 2016 (doi:10.1007/978-3-319-50106-2_37). doi:10.1016/J.TCS.2019.11.024.
  3. Radial level planarity testing and embedding in linear time. J. Graph Algorithms Appl., 9(1):53--97, 2005. doi:10.7155/jgaa.00100.
  4. Linear time planarity testing and embedding of strongly connected cyclic level graphs. In Dan Halperin and Kurt Mehlhorn, editors, Proc. 16th Ann. European Sympos. Algorithms (ESA), volume 5193 of LNCS, pages 136--147. Springer, 2008. doi:10.1007/978-3-540-87744-8_12.
  5. XNLP-completeness for parameterized problems on graphs with a linear structure. In Holger Dell and Jesper Nederlof, editors, 17th Int. Symp. Param. Exact Comput. (IPEC), volume 249 of LIPIcs, pages 8:1--8:18. Schloss Dagstuhl -- Leibniz-Zentrum fĂźr Informatik, 2022. doi:10.4230/LIPIcs.IPEC.2022.8.
  6. Parameterized problems complete for nondeterministic FPT time and logarithmic space. In Proc. 62nd Ann. IEEE Symp. Foundat. Comput. Sci. (FOCS), pages 193--204, 2022. doi:10.1109/FOCS52979.2021.00027.
  7. Partial and constrained level planarity. In Philip N. Klein, editor, Proc. 28th Ann. ACM-SIAM Symp. Discrete Algorithms (SODA), pages 2000--2011. SIAM, 2017. doi:10.1137/1.9781611974782.130.
  8. An SPQR-tree-like embedding representation for level planarity. In Yixin Cao, Siu-Wing Cheng, and Minming Li, editors, Proc. 31st Int. Symp. Algorithms Comput. (ISAAC), volume 181 of LIPIcs, pages 8:1--8:15. Schloss Dagstuhl -- Leibniz-Zentrum fßr Informatik, 2020. doi:10.4230/LIPIcs.ISAAC.2020.8.
  9. Parameterized Algorithms. Springer, Cham, 2015. doi:10.1007/978-3-319-21275-3.
  10. Giuseppe Di Battista and Enrico Nardelli. Hierarchies and planarity theory. IEEE Trans. Systems, Man, and Cybernetics, 18(6):1035--1046, 1988. doi:10.1109/21.23105.
  11. On the parameterized complexity of layered graph drawing. Algorithmica, 52:267--292, 2008. doi:10.1007/s00453-007-9151-1.
  12. On the space and circuit complexity of parameterized problems: Classes and completeness. Algorithmica, 71(3):661--701, 2015. doi:10.1007/s00453-014-9944-y.
  13. On the parameterized complexity of multiple-interval graph problems. Theor. Comput. Sci., 410(1):53--61, 2009. doi:10.1016/j.tcs.2008.09.065.
  14. Clustered level planarity. In Peter van Emde Boas, Jaroslav Pokorný, Måria Bielikovå, and Julius Stuller, editors, Proc. 30th Conf. Curr. Trends Theory & Practice Comput. Sci. (SOFSEM), volume 2932 of LNCS, pages 218--228. Springer, 2004. doi:10.1007/978-3-540-24618-3_18.
  15. Hanani--Tutte, monotone drawings, and level-planarity. In Thirty Essays on Geometric Graph Theory, pages 263--287. Springer, 2013. doi:10.1007/978-1-4614-0110-0_14.
  16. Complexity results for multiprocessor scheduling under resource constraints. SIAM J. Comput., 4(4):397--411, 1975. doi:10.1137/0204035.
  17. On the computational complexity of upward and rectilinear planarity testing. SIAM J. Comput., 31(2):601--625, 2001. Conference version in Proc. GD 1994 (doi:10.1007/3-540-58950-3_384). doi:10.1137/S0097539794277123.
  18. Trees with Hamiltonian square. Mathematika, 18(1):138--140, 1971. doi:10.1112/S0025579300008494.
  19. Recognizing leveled-planar dags in linear time. In Franz-Josef Brandenburg, editor, Proc. Int. Symp. Graph Drawing (GD), volume 1027 of LNCS, pages 300--311. Springer, 1995. doi:10.1007/BFb0021813.
  20. Convex drawings of hierarchical planar graphs and clustered planar graphs. J. Discrete Algorithms, 8(3):282--295, 2010. doi:10.1016/j.jda.2009.05.003.
  21. Pitfalls of using PQ-trees in automatic graph drawing. In Giuseppe Di Battista, editor, Proc. 5th Int. Symp. Graph Drawing (GD), volume 1353 of LNCS, pages 193--204. Springer, 1997. doi:10.1007/3-540-63938-1_62.
  22. Level planarity testing in linear time. In Sue Whitesides, editor, Proc. 6th Int. Symp. Graph Drawing (GD), volume 1547 of LNCS, pages 224--237. Springer, 1998. doi:10.1007/3-540-37623-2_17.
  23. Boris Klemz. Convex drawings of hierarchical graphs in linear time, with applications to planar graph morphing. In Petra Mutzel, Rasmus Pagh, and Grzegorz Herman, editors, Proc. 29th Ann. Europ. Symp. Algorithms (ESA), volume 204 of LIPIcs, pages 57:1--57:15. Schloss Dagstuhl -- Leibniz-Zentrum fßr Informatik, 2021. doi:10.4230/LIPIcs.ESA.2021.57.
  24. Ordered level planarity and its relationship to geodesic planarity, bi-monotonicity, and variations of level planarity. ACM Trans. Algorithms, 15(4):53:1--53:25, 2019. Conference version in Proc. GD 2017 (doi:10.1007/978-3-319-73915-1_34). doi:10.1145/3359587.
  25. Krzysztof Pietrzak. On the parameterized complexity of the fixed alphabet shortest common supersequence and longest common subsequence problems. J. Comput. Syst. Sci., 67(4):757--771, 2003. doi:10.1016/S0022-0000(03)00078-3.
  26. Ignaz Rutter. Personal communication, 2022.
  27. Robert Tarjan. Depth-first search and linear graph algorithms. SIAM Journal on Computing, 1(2):146--160, 1972. doi:10.1137/0201010.
  28. Generalized k𝑘kitalic_k-ary tanglegrams on level graphs: A satisfiability-based approach and its evaluation. Discrete Appl. Math., 160(16-17):2349--2363, 2012. doi:10.1016/j.dam.2012.05.028.
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