Algorithms for Incremental Planar Graph Drawing and Two-page Book Embeddings

Subject of this work are two problems related to ordering the vertices of planar graphs. The first one is concerned with the properties of vertex-orderings that serve as a basis for incremental drawing algorithms. Such a drawing algorithm usually extends a drawing by adding the vertices step-by-step as provided by the ordering. In the field of graph drawing several orderings are in use for this purpose. Some of them, however, lack certain properties that are desirable or required for classic incremental drawing methods. We narrow down these properties, and introduce the bitonic st-ordering, an ordering which combines the features only available when using canonical orderings with the flexibility of st-orderings. The additional property of being bitonic enables an st-ordering to be used in algorithms that usually require a canonical ordering. With this in mind, we describe a linear-time algorithm that computes such an ordering for every biconnected planar graph. Unlike canonical orderings, st-orderings extend to directed graphs, in particular planar st-graphs. Being able to compute bitonic st-orderings for planar st-graphs is of particular interest for upward planar drawing algorithms, since traditional incremental algorithms for undirected planar graphs might be adapted to directed graphs. Based on this observation, we give a full characterization of the class of planar st-graphs that admit such an ordering. This includes a linear-time algorithm for recognition and ordering. Furthermore, we show that by splitting specific edges of an instance that is not part of this class, one is able to transform it into one for which then such an ordering exists. To do so, we describe a linear-time algorithm for finding the smallest set of edges to split. We show that for a planar st-graph G=(V,E), |V|−3 edge splits are sufficient and every edge is split at most once. This immediately translates to the number of bends required for upward planar poly-line drawings. More specifically, we show that every planar st-graph admits an upward planar poly-line drawing in quadratic area with at most |V|−3 bends in total and at most one bend per edge. Moreover, the drawing can be obtained in linear time. The second part is concerned with embedding planar graphs with maximum degree three and four into books. Besides providing a simplified incremental linear-time algorithm for embedding triconnected 3-planar graphs into a book of two pages, we describe a linear-time algorithm to compute a subhamiltonian cycle in a triconnected 4-planar graph

Fully Scalable Massively Parallel Algorithms for Embedded Planar Graphs

We consider the massively parallel computation (MPC) model, which is a theoretical abstraction of large-scale parallel processing models such as MapReduce. In this model, assuming the widely believed 1-vs-2-cycles conjecture, solving many basic graph problems in $O(1)$ rounds with a strongly sublinear memory size per machine is impossible. We improve on the recent work of Holm and T\v{e}tek [SODA 2023] that bypass this barrier for problems when a planar embedding of the graph is given. In the previous work, on graphs of size $n$ with $O(n/\mathcal{S})$ machines, the memory size per machine needs to be at least $\mathcal{S} = n^{2/3+\Omega(1)}$, whereas we extend their work to the fully scalable regime, where the memory size per machine can be $\mathcal{S} = n^{\delta}$ for any constant $0< \delta < 1$. We give the first constant round fully scalable algorithms for embedded planar graphs for the problems of (i) connectivity and (ii) minimum spanning tree (MST). Moreover, we show that the $\varepsilon$-emulator of Chang, Krauthgamer, and Tan [STOC 2022] can be incorporated into our recursive framework to obtain constant-round $(1+\varepsilon)$-approximation algorithms for the problems of computing (iii) single source shortest path (SSSP), (iv) global min-cut, and (v) $st$-max flow. All previous results on cuts and flows required linear memory in the MPC model. Furthermore, our results give new algorithms for problems that implicitly involve embedded planar graphs. We give as corollaries constant round fully scalable algorithms for (vi) 2D Euclidean MST using $O(n)$ total memory and (vii) $(1+\varepsilon)$-approximate weighted edit distance using $\widetilde{O}(n^{2-\delta})$ memory. Our main technique is a recursive framework combined with novel graph drawing algorithms to compute smaller embedded planar graphs in constant rounds in the fully scalable setting.Comment: To appear in SODA24. 55 pages, 9 figures, 1 table. Added section on weighted edit distance and shortened abstrac

Bar 1-Visibility Drawings of 1-Planar Graphs

A bar 1-visibility drawing of a graph $G$ is a drawing of $G$ where each vertex is drawn as a horizontal line segment called a bar, each edge is drawn as a vertical line segment where the vertical line segment representing an edge must connect the horizontal line segments representing the end vertices and a vertical line segment corresponding to an edge intersects at most one bar which is not an end point of the edge. A graph $G$ is bar 1-visible if $G$ has a bar 1-visibility drawing. A graph $G$ is 1-planar if $G$ has a drawing in a 2-dimensional plane such that an edge crosses at most one other edge. In this paper we give linear-time algorithms to find bar 1-visibility drawings of diagonal grid graphs and maximal outer 1-planar graphs. We also show that recursive quadrangle 1-planar graphs and pseudo double wheel 1-planar graphs are bar 1-visible graphs.Comment: 15 pages, 9 figure

A Note on the Practicality of Maximal Planar Subgraph Algorithms

Given a graph $G$, the NP-hard Maximum Planar Subgraph problem (MPS) asks for a planar subgraph of $G$ with the maximum number of edges. There are several heuristic, approximative, and exact algorithms to tackle the problem, but---to the best of our knowledge---they have never been compared competitively in practice. We report on an exploratory study on the relative merits of the diverse approaches, focusing on practical runtime, solution quality, and implementation complexity. Surprisingly, a seemingly only theoretically strong approximation forms the building block of the strongest choice.Comment: Appears in the Proceedings of the 24th International Symposium on Graph Drawing and Network Visualization (GD 2016

L-Visibility Drawings of IC-planar Graphs

An IC-plane graph is a topological graph where every edge is crossed at most once and no two crossed edges share a vertex. We show that every IC-plane graph has a visibility drawing where every vertex is an L-shape, and every edge is either a horizontal or vertical segment. As a byproduct of our drawing technique, we prove that an IC-plane graph has a RAC drawing in quadratic area with at most two bends per edge

Optimal Morphs of Convex Drawings

We give an algorithm to compute a morph between any two convex drawings of the same plane graph. The morph preserves the convexity of the drawing at any time instant and moves each vertex along a piecewise linear curve with linear complexity. The linear bound is asymptotically optimal in the worst case.Comment: To appear in SoCG 201

Small Superpatterns for Dominance Drawing

We exploit the connection between dominance drawings of directed acyclic graphs and permutations, in both directions, to provide improved bounds on the size of universal point sets for certain types of dominance drawing and on superpatterns for certain natural classes of permutations. In particular we show that there exist universal point sets for dominance drawings of the Hasse diagrams of width-two partial orders of size O(n^{3/2}), universal point sets for dominance drawings of st-outerplanar graphs of size O(n\log n), and universal point sets for dominance drawings of directed trees of size O(n^2). We show that 321-avoiding permutations have superpatterns of size O(n^{3/2}), riffle permutations (321-, 2143-, and 2413-avoiding permutations) have superpatterns of size O(n), and the concatenations of sequences of riffles and their inverses have superpatterns of size O(n\log n). Our analysis includes a calculation of the leading constants in these bounds.Comment: ANALCO 2014, This version fixes an error in the leading constant of the 321-superpattern siz