Drawing Planar Graphs Using the Canonical Ordering

We consider dynamic subgraph connectivity problems for planar undirected graphs. In this model there is a fixed underlying planar graph, where each edge and vertex is either off (failed) or (recovered). We wish to answer connectivity queries with respect to the subgraph. The model has two natural variants, one in which there are d edge/vertex failures that precede all connectivity queries, and one in which failures/recoveries and queries are intermixed. We present a d-failure connectivity oracle for planar graphs that processes any d edge/vertex failures in sort(d,n) time so that connectivity queries can be answered in pred(d,n) time. (Here sort and pred are the time for integer sorting and integer predecessor search over a subset of [n] of size d.) Our algorithm has two discrete parts. The first is an algorithm tailored to triconnected planar graphs. It makes use of Barnette's theorem, which states that every triconnected planar graph contains a degree-3 spanning tree. The second part is a generic reduction from general (planar) graphs to triconnected (planar) graphs. Our algorithm is, moreover, provably optimal. An implication of Pǎtrascu and Thorup's lower bound on predecessor search is that no d-failure connectivity oracle (even on trees) can beat pred(d,n) query time. We extend our algorithms to the subgraph connectivity model where edge/vertex failures (but no recoveries) are intermixed with connectivity queries. In triconnected planar graphs each failure and query is handled in O(logn) time (amortized), whereas in general planar graphs both bounds become O(log2n).

The $(\Delta,D)$ (degree/diameter) problem consists of finding the largest possible number of vertices $n$ among all the graphs with maximum degree $\Delta$ and diameter $D$. We consider the $(\Delta,D)$ problem for maximal planar bipartite graphs, that is, simple planar graphs in which every face is a quadrangle. We obtain that for the $(\Delta,2)$ problem, the number of vertices is $n=\Delta+2$; and for the $(\Delta,3)$ problem, $n= 3\Delta-1$ if $\Delta$ is odd and $n= 3\Delta-2$ if $\Delta$ is even. Then, we prove that, for the general case of the $(\Delta,D)$ problem, an upper bound on $n$ is approximately $3(2D+1)(\Delta-2)^{\lfloor D/2\rfloor}$, and another one is $C(\Delta-2)^{\lfloor D/2\rfloor}$ if $\Delta\geq D$ and $C$ is a sufficiently large constant. Our upper bounds improve for our kind of graphs the one given by Fellows, Hell and Seyffarth for general planar graphs. We also give a lower bound on $n$ for maximal planar bipartite graphs, which is approximately $(\Delta-2)^{k}$ if $D=2k$, and $3(\Delta-3)^k$ if $D=2k+1$, for $\Delta$ and $D$ sufficiently large in both cases.

An orthogonal drawing of a graph is a drawing such that nodes are placed on grid points and edges are drawn as sequences of vertical and horizontal segments. In this paper we present linear time algorithms that produce orthogonal drawings of graphs with n nodes. If the maximum degree is four, then the drawing produced by our algorithm needs area no greater than 0.8n2 and no more than 1.9n bends. Notice that our upper bound on the bends is below the lower bound for planar orthogonal drawings of planar graphs. To the best of our knowledge, this is the first algorithm for orthogonal drawings that needs area less than n2. If the maximum degree is three, then the drawing produced by our algorithm needs (n/2+1)×n/2 area and at most n/2+3 bends. These upper bounds match the upper bounds known for triconnected planar graphs of degree 3.

In a convex grid drawing of a plane graph, every edge is drawn as a straight-line segment without any edge-intersection, every vertex is located at a grid point, and every facial cycle is drawn as a convex polygon. A plane graph G has a convex drawing if and only if G is internally triconnected. It has been known that an internally triconnected plane graph G of n vertices has a convex grid drawing on a grid of O(n 3) area if the triconnected component decomposition tree of G has at most four leaves. In this paper, we improve the area bound O(n 3) to O(n 2), which is optimal up to a constant factor. More precisely, we show that G has a convex grid drawing on a 2n×4n grid. We also present an algorithm to find such a drawing in linear time.

We investigate open rectangle-of-influence drawings for irreducible triangulations, which are plane graphs with a quadrangular exterior face, triangular interior faces and no separating triangles. An open rectangle-of-influence drawing of a plane graph G is a type of straight-line grid drawing where there is no vertices drawn in the proper inside of the axis-parallel rectangle defined by the two end vertices of any edge. The algorithm presented by Miura and Nishizeki [8] uses a grid of size \({\cal W} + {\cal H} \leq\) (n-1), where \({\cal W}\) is the width of the grid, \({\cal H}\) is the height of the grid and n is the number of vertices in G. Thus the area of the grid is at most ⌈(n-1)/2⌉ × \(\lfloor\)(n-1)/2\(\rfloor\) [8].In this paper, we prove that the two straight-line grid drawing algorithms for irreducible triangulations from [4] and quadrangulations from [3,5] actually produce open rectangle-of-influence drawings for them respectively. Therefore, the straight-line grid drawing size bounds from [3,4,5] also hold for the open rectangle-of-influence drawings. For irreducible triangulations, the new asymptotical grid size bound is \(\emph{11n/27}\) × \(\emph{11n/27}\). For quadrangulations, our asymptotical grid size bound \(\emph{13n/27}\) × \(\emph{13n/27}\) is the first known such bound.KeywordsPlane GraphInterior VertexTransversal StructureBlue EdgeIrreducible TriangulationThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

An octilinear drawing of a planar graph is one in which each edge is drawn as a sequence of horizontal, vertical and diagonal at $45^\circ$ and $-45^\circ$ line-segments. For such drawings to be readable, special care is needed in order to keep the number of bends small. Since the problem of finding planar octilinear drawings with minimum number of bends is NP-hard, in this paper we focus on upper and lower bounds. From a recent result of Keszegh et al. on the slope number of planar graphs, we can derive an upper bound of $4n-10$ bends for planar graphs with $n$ vertices and maximum degree $8$. We considerably improve this general bound and corresponding previous ones for triconnected planar graphs of maximum degree $4$, $5$ and $6$. We also derive non-trivial lower bounds for these three classes of graphs by a technique inspired by the network flow formulation of Tamassia for computing bend optimal orthogonal drawings.

We show that the 1-planar slope number of 3-connected cubic 1-planar graphs is at most 4 when edges are drawn as polygonal curves with at most 1 bend each. This bound is obtained by drawings whose vertex and crossing resolution is at least \(\pi /4\). On the other hand, if the embedding is fixed, then there is a 3-connected cubic 1-planar graph that needs 3 slopes when drawn with at most 1 bend per edge. We also show that 2 slopes always suffice for 1-planar drawings of subcubic 1-planar graphs with at most 2 bends per edge. This bound is obtained with vertex resolution \(\pi /2\) and the drawing is RAC (crossing resolution \(\pi /2\)). Finally, we prove lower bounds for the slope number of straight-line 1-planar drawings in terms of number of vertices and maximum degree.

Equitable colorings of planar graphs with maximum degree at least nine

On The Number of Subgraphs of Prescribed Type of Planar Graphs With A Given Number of Vertices

Edge Separators of Planar and Outerplanar Graphs With Applications

In [JM94] we used a branch and cut algorithm in order to determine a maximum weight planar subgraph of a given graph. One of the motivations was to produce a nice drawing of a given graph by drawing the found maximum planar subgraph, and then augmenting this drawing by the removed edges. Our experiments indicate that drawing algorithms for planar graphs which require 2- or 3-connectivity, resp. degree-constraints, in addition to planarity often give “nicer” results. Thus we are led to the following problems: (1) Find a maximum planar subgraph with maximum degree d ∈ IN. (2) Augment a planar graph to a K-connected planar graph. (3) Find a maximum planar k-connected subgraph of a given k-connected graph. (4) Given a graph G, which is not necessarily planar and not necessarily k-connected, determine a new graph H by removing r edges and adding a edges such that the new graph H is planar, spanning, k-connected, each node v has degree at most D(v) and r+a is minimum. Problems (1), (2) and (3) have been discussed in the literature, we argue that a solution to the newly defined problem (4) is most useful for our goal. For all four problems we give a polyhedral formulation by defining different linear objective functions over the same polytope which is the intersection of the planar subgraph polytope [JM93], the k-connected subgraph polytope [S92] and the degree-constrained subgraph polytope. We point out why we are confident that a branch and cut algorithm for the new problem will be an implementable and useful tool in automatic graph drawing.KeywordsPlanar GraphInteger PointIncidence VectorSubgraph ProblemNonplanar GraphThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

River routing in VLSI and the one‐layer wire routing problem for printed circuit boards can be formulated as a problem of finding a forest in a planar (grid) graph. Given a planar graph G representing a wiring region and sets of terminals to be equipotential (that is, nets), we want to find vertex‐disjoint trees (i.e., a forest), each of which interconnects terminals of each net. This paper presents an algorithm for solving the forementioned problem in O (MIN {kn, n log n}) time when terminals of nets are placed on the two faces of a planar graph G, where n is the number of vertices of G, and k, that of nets.

A straight line drawing of a graph is an open weak rectangle-of-influence (RI) drawing if there is no vertex in the relative interior of the axis parallel rectangle induced by the end points of each edge. Despite recent interest of the graph drawing community in rectangle-of-influence drawings, no algorithm is known to test whether a graph has a planar open weak RI-drawing.In a recent paper, we showed how to test, for inner-triangulated planar graphs, whether they have a planar open weak RI-drawing with a non-aligned frame, i.e., the graph obtained from removing the interior of every filled triangle is drawn such that no two vertices have the same coordinate. In this paper, we generalize this to all planar graphs with a fixed planar embedding, even if some interior faces are not triangles. On the other hand, we show that if the planar embedding is not fixed, then deciding if a given planar graph has an open weak RI-drawing is NP-complete. NP-completeness holds even for open weak RI-drawings with non-aligned frames.KeywordsProximity drawingsRectangle-of-Influence drawingsAngular labeling

Plane graphs with maximum degree 9 are entirely 11-choosable

The geometric simultaneous embedding problem asks whether two planar graphs on the same set of vertices in the plane can be drawn using straight lines, such that each graph is plane. Geometric simultaneous embedding is a current topic in graph drawing and positive and negative results are known for various classes of graphs. So far only connected graphs have been considered. In this paper we present the first results for the setting where one of the graphs is a matching. In particular, we show that there exist a planar graph and a matching which do not admit a geometric simultaneous embedding. This strengthens an analogous negative result for a planar graph and a path. On the positive side, we describe algorithms that compute a geometric simultaneous embedding of a matching and a wheel, outerpath, or tree. Our drawing algorithms minimize the number of orientations used to draw the edges of the matching. Specifically, when embedding a matching and a tree, we can draw all matching edges horizontally. When embedding a matching and a wheel or an outerpath, we use only two orientations.