Faster Separators for Shallow Minor-Free Graphs via Dynamic Approximate Distance Oracles

Plotkin, Rao, and Smith (SODA'97) showed that any graph with $m$ edges and $n$ vertices that excludes $K_h$ as a depth $O(\ell\log n)$-minor has a separator of size $O(n/\ell + \ell h^2\log n)$ and that such a separator can be found in $O(mn/\ell)$ time. A time bound of $O(m + n^{2+\epsilon}/\ell)$ for any constant $\epsilon > 0$ was later given (W., FOCS'11) which is an improvement for non-sparse graphs. We give three new algorithms. The first has the same separator size and running time O(\mbox{poly}(h)\ell m^{1+\epsilon}). This is a significant improvement for small $h$ and $\ell$. If $\ell = \Omega(n^{\epsilon'})$ for an arbitrarily small chosen constant $\epsilon' > 0$, we get a time bound of O(\mbox{poly}(h)\ell n^{1+\epsilon}). The second algorithm achieves the same separator size (with a slightly larger polynomial dependency on $h$) and running time O(\mbox{poly}(h)(\sqrt\ell n^{1+\epsilon} + n^{2+\epsilon}/\ell^{3/2})) when $\ell = \Omega(n^{\epsilon'})$. Our third algorithm has running time O(\mbox{poly}(h)\sqrt\ell n^{1+\epsilon}) when $\ell = \Omega(n^{\epsilon'})$. It finds a separator of size O(n/\ell) + \tilde O(\mbox{poly}(h)\ell\sqrt n) which is no worse than previous bounds when $h$ is fixed and $\ell = \tilde O(n^{1/4})$. A main tool in obtaining our results is a novel application of a decremental approximate distance oracle of Roditty and Zwick.Comment: 16 pages. Full version of the paper that appeared at ICALP'14. Minor fixes regarding the time bounds such that these bounds hold also for non-sparse graph

Engineering Planar Separator Algorithms

We consider classical linear-time planar separator algorithms, determining for a given planar graph a small subset of the nodes whose removal separates the graph into two components of similar size. These algorithms are based upon Planar Separator Theorems, which guarantee separators of size asymptotically in the square root of the number of nodes n and remaining components of size less than 2n/3. In this work, we present a comprehensive experimental study of the algorithms applied to a large variety of graphs, where the main goal is to find separators that do not only satisfy upper bounds but also possess other desirable qualities with respect to separator size and component balance. We propose the usage of fundamental cycles, whose size is at most twice the diameter of the graph, as planar separators: For graphs of small diameter the guaranteed bound is better than the bounds of the classical algorithms, and it turns out that this simple strategy almost always outperforms the other algorithms, even for graphs with large diameter

Achieving Good Angular Resolution in 3D Arc Diagrams

We study a three-dimensional analogue to the well-known graph visualization approach known as arc diagrams. We provide several algorithms that achieve good angular resolution for 3D arc diagrams, even for cases when the arcs must project to a given 2D straight-line drawing of the input graph. Our methods make use of various graph coloring algorithms, including an algorithm for a new coloring problem, which we call localized edge coloring.Comment: 12 pages, 5 figures; to appear at the 21st International Symposium on Graph Drawing (GD 2013

A Planarity Test via Construction Sequences

Optimal linear-time algorithms for testing the planarity of a graph are well-known for over 35 years. However, these algorithms are quite involved and recent publications still try to give simpler linear-time tests. We give a simple reduction from planarity testing to the problem of computing a certain construction of a 3-connected graph. The approach is different from previous planarity tests; as key concept, we maintain a planar embedding that is 3-connected at each point in time. The algorithm runs in linear time and computes a planar embedding if the input graph is planar and a Kuratowski-subdivision otherwise

Graph Separators: A Parameterized View

Graph separation is a well-known tool to make (hard) graph problems accessible to a divide and conquer approach. We show how to use graph separator theorems in combination with (linear) problem kernels in order to develop fixed parameter algorithms for many well-known NP-hard (planar) graph problems. We coin the key notion of glueable select&verify graph problems and derive from that a prospective way to easily check whether a planar graph problem will allow for a xed parameter algorithm of running time c p k n O(1) for constant c. Besides, we introduce the novel concept of "problem cores" that might serve as an alternative to problem kernels for devising parameterized algorithms. One of the main contributions of the paper is to exactly compute the base c of the exponential term and its dependence on the various parameters specified by the employed separator theorem and the underlying graph problem. We discuss several strategies to improve on the involved constant c. Our findings also give rise to studying further renements of the complexity class FPT of fixed parameter tractable problems

On Drawing a Graph Convexly in the Plane (Extended Abstract)

) ? Hristo N. Djidjev Department of Computer Science, Rice University, Hoston, TX 77251, USA Abstract. Let G be a planar graph and H be a subgraph of G. Given any convex drawing of H, we investigate the problem of how to extend the drawing of H to a convex drawing of G. We obtain a necessary and sufficient condition for the existence and a linear algorithm for the construction of such an extension. Our results and their corollaries generalize previous theoretical and algorithmic results of Tutte, Thomassen, Chiba, Yamanouchi, and Nishizeki. 1 Introduction The problem of embedding of a graph in the plane so that the resulting drawing has nice geometric properties has received recently significant attention. This is due to the large number of applications including circuit and VLSI design, algorithm animation, information systems design and analysis. The reader is referred to [1] for annotated bibliography on graph drawings. The first linear-time algorithm for testing a graph for plan..