81 research outputs found

    Planarity of Streamed Graphs

    Full text link
    In this paper we introduce a notion of planarity for graphs that are presented in a streaming fashion. A streamed graph\textit{streamed graph} is a stream of edges e1,e2,...,eme_1,e_2,...,e_m on a vertex set VV. A streamed graph is ω\omega-stream planar\textit{stream planar} with respect to a positive integer window size ω\omega if there exists a sequence of planar topological drawings Γi\Gamma_i of the graphs Gi=(V,{ej∣i≤j<i+ω})G_i=(V,\{e_j \mid i\leq j < i+\omega\}) such that the common graph G∩i=Gi∩Gi+1G^{i}_\cap=G_i\cap G_{i+1} is drawn the same in Γi\Gamma_i and in Γi+1\Gamma_{i+1}, for 1≤i<m−ω1\leq i < m-\omega. The Stream Planarity\textit{Stream Planarity} Problem with window size ω\omega asks whether a given streamed graph is ω\omega-stream planar. We also consider a generalization, where there is an additional backbone graph\textit{backbone graph} whose edges have to be present during each time step. These problems are related to several well-studied planarity problems. We show that the Stream Planarity\textit{Stream Planarity} Problem is NP-complete even when the window size is a constant and that the variant with a backbone graph is NP-complete for all ω≥2\omega \ge 2. On the positive side, we provide O(n+ωm)O(n+\omega{}m)-time algorithms for (i) the case ω=1\omega = 1 and (ii) all values of ω\omega provided the backbone graph consists of one 22-connected component plus isolated vertices and no stream edge connects two isolated vertices. Our results improve on the Hanani-Tutte-style O((nm)3)O((nm)^3)-time algorithm proposed by Schaefer [GD'14] for ω=1\omega=1.Comment: 21 pages, 9 figures, extended version of "Planarity of Streamed Graphs" (9th International Conference on Algorithms and Complexity, 2015

    Computing k-Modal Embeddings of Planar Digraphs

    Get PDF
    Given a planar digraph G and a positive even integer k, an embedding of G in the plane is k-modal, if every vertex of G is incident to at most k pairs of consecutive edges with opposite orientations, i.e., the incoming and the outgoing edges at each vertex are grouped by the embedding into at most k sets of consecutive edges with the same orientation. In this paper, we study the k-Modality problem, which asks for the existence of a k-modal embedding of a planar digraph. This combinatorial problem is at the very core of a variety of constrained embedding questions for planar digraphs and flat clustered networks. First, since the 2-Modality problem can be easily solved in linear time, we consider the general k-Modality problem for any value of k>2 and show that the problem is NP-complete for planar digraphs of maximum degree Delta <= k+3. We relate its computational complexity to that of two notions of planarity for flat clustered networks: Planar Intersection-Link and Planar NodeTrix representations. This allows us to answer in the strongest possible way an open question by Di Giacomo [https://doi.org/10.1007/978-3-319-73915-1_37], concerning the complexity of constructing planar NodeTrix representations of flat clustered networks with small clusters, and to address a research question by Angelini et al. [https://doi.org/10.7155/jgaa.00437], concerning intersection-link representations based on geometric objects that determine complex arrangements. On the positive side, we provide a simple FPT algorithm for partial 2-trees of arbitrary degree, whose running time is exponential in k and linear in the input size. Second, motivated by the recently-introduced planar L-drawings of planar digraphs [https://doi.org/10.1007/978-3-319-73915-1_36], which require the computation of a 4-modal embedding, we focus our attention on k=4. On the algorithmic side, we show a complexity dichotomy for the 4-Modality problem with respect to Delta, by providing a linear-time algorithm for planar digraphs with Delta <= 6. This algorithmic result is based on decomposing the input digraph into its blocks via BC-trees and each of these blocks into its triconnected components via SPQR-trees. In particular, we are able to show that the constraints imposed on the embedding by the rigid triconnected components can be tackled by means of a small set of reduction rules and discover that the algorithmic core of the problem lies in special instances of NAESAT, which we prove to be always NAE-satisfiable - a result of independent interest that improves on Porschen et al. [https://doi.org/10.1007/978-3-540-24605-3_14]. Finally, on the combinatorial side, we consider outerplanar digraphs and show that any such a digraph always admits a k-modal embedding with k=4 and that this value of k is best possible for the digraphs in this family

    Approximation Algorithms for Facial Cycles in Planar Embeddings

    Get PDF
    Consider the following combinatorial problem: Given a planar graph G and a set of simple cycles C in G, find a planar embedding E of G such that the number of cycles in C that bound a face in E is maximized. This problem, called Max Facial C-Cycles, was first studied by Mutzel and Weiskircher [IPCO \u2799, http://dx.doi.org/10.1007/3-540-48777-8_27) and then proved NP-hard by Woeginger [Oper. Res. Lett., 2002, http://dx.doi.org/10.1016/S0167-6377(02)00119-0]. We establish a tight border of tractability for Max Facial C-Cycles in biconnected planar graphs by giving conditions under which the problem is NP-hard and showing that strengthening any of these conditions makes the problem polynomial-time solvable. Our main results are approximation algorithms for Max Facial C-Cycles. Namely, we give a 2-approximation for series-parallel graphs and a (4+epsilon)-approximation for biconnected planar graphs. Remarkably, this provides one of the first approximation algorithms for constrained embedding problems

    Clustered Planarity with Pipes

    Get PDF
    We study the version of the C-Planarity problem in which edges connecting the same pair of clusters must be grouped into pipes, which generalizes the Strip Planarity problem. We give algorithms to decide several families of instances for the two variants in which the order of the pipes around each cluster is given as part of the input or can be chosen by the algorithm

    Strip Planarity Testing of Embedded Planar Graphs

    Full text link
    In this paper we introduce and study the strip planarity testing problem, which takes as an input a planar graph G(V,E)G(V,E) and a function γ:V→{1,2,…,k}\gamma:V \rightarrow \{1,2,\dots,k\} and asks whether a planar drawing of GG exists such that each edge is monotone in the yy-direction and, for any u,v∈Vu,v\in V with γ(u)<γ(v)\gamma(u)<\gamma(v), it holds y(u)<y(v)y(u)<y(v). The problem has strong relationships with some of the most deeply studied variants of the planarity testing problem, such as clustered planarity, upward planarity, and level planarity. We show that the problem is polynomial-time solvable if GG has a fixed planar embedding.Comment: 24 pages, 12 figures, extended version of 'Strip Planarity Testing' (21st International Symposium on Graph Drawing, 2013

    Advancements on SEFE and Partitioned Book Embedding Problems

    Full text link
    In this work we investigate the complexity of some problems related to the {\em Simultaneous Embedding with Fixed Edges} (SEFE) of kk planar graphs and the PARTITIONED kk-PAGE BOOK EMBEDDING (PBE-kk) problems, which are known to be equivalent under certain conditions. While the computational complexity of SEFE for k=2k=2 is still a central open question in Graph Drawing, the problem is NP-complete for k≥3k \geq 3 [Gassner {\em et al.}, WG '06], even if the intersection graph is the same for each pair of graphs ({\em sunflower intersection}) [Schaefer, JGAA (2013)]. We improve on these results by proving that SEFE with k≥3k \geq 3 and sunflower intersection is NP-complete even when the intersection graph is a tree and all the input graphs are biconnected. Also, we prove NP-completeness for k≥3k \geq 3 of problem PBE-kk and of problem PARTITIONED T-COHERENT kk-PAGE BOOK EMBEDDING (PTBE-kk) - that is the generalization of PBE-kk in which the ordering of the vertices on the spine is constrained by a tree TT - even when two input graphs are biconnected. Further, we provide a linear-time algorithm for PTBE-kk when k−1k-1 pages are assigned a connected graph. Finally, we prove that the problem of maximizing the number of edges that are drawn the same in a SEFE of two graphs is NP-complete in several restricted settings ({\em optimization version of SEFE}, Open Problem 99, Chapter 1111 of the Handbook of Graph Drawing and Visualization).Comment: 29 pages, 10 figures, extended version of 'On Some NP-complete SEFE Problems' (Eighth International Workshop on Algorithms and Computation, 2014

    Graph Product Structure for h-Framed Graphs

    Get PDF
    Graph product structure theory expresses certain graphs as subgraphs of the strong product of much simpler graphs. In particular, an elegant formulation for the corresponding structural theorems involves the strong product of a path and of a bounded treewidth graph, and allows to lift combinatorial results for bounded treewidth graphs to graph classes for which the product structure holds, such as to planar graphs [Dujmovi? et al., J. ACM, 67(4), 22:1-38, 2020]. In this paper, we join the search for extensions of this powerful tool beyond planarity by considering the h-framed graphs, a graph class that includes 1-planar, optimal 2-planar, and k-map graphs (for appropriate values of h). We establish a graph product structure theorem for h-framed graphs stating that the graphs in this class are subgraphs of the strong product of a path, of a planar graph of treewidth at most 3, and of a clique of size 3? h/2 ?+? h/3 ?-1. This allows us to improve over the previous structural theorems for 1-planar and k-map graphs. Our results constitute significant progress over the previous bounds on the queue number, non-repetitive chromatic number, and p-centered chromatic number of these graph classes, e.g., we lower the currently best upper bound on the queue number of 1-planar graphs and k-map graphs from 115 to 82 and from ? 33/2(k+3 ? k/2? -3)? to ? 33/2 (3? k/2 ?+? k/3 ?-1) ?, respectively. We also employ the product structure machinery to improve the current upper bounds on the twin-width of 1-planar graphs from O(1) to 80. All our structural results are constructive and yield efficient algorithms to obtain the corresponding decompositions
    • …
    corecore