Abstract:We present a cubic-time algorithm for the following problem: Given a simple graph, decide whether it is realized by adjacencies of countries in a map without holes, in which at most four countries meet at any point.
“…10a by exchanging edges ( p, s), (c, h) and ( p, h), (c, s). Consider candidate c in B 17 . Then H (c) = (2, 3, 4, 4, 4, 5, 6) violates optimal 1-planarity.…”
Section: Discussionmentioning
confidence: 99%
“…In his introductory paper on 1-planar graphs, Ringel studied the coloring problem and observed that a pair of crossing edges can be completed to K 4 by adding planar edges. 1-Planar graphs generalize 4-map graphs, which are the graphs of adjacencies of nations of a map [16,17]. Two nations are adjacent if they share a The first study of structural properties of 1-planar graphs is by Bodendiek, Schumacher, and Wagner [7,8].…”
Section: Introductionmentioning
confidence: 99%
“…A 1-planar graph G is maximally dense or maximum [36] if there is no 1-planar graph of the same size with more edges. It is maximal 1-planar if the addition of any edge destroys 1-planarity and planar-maximal or triangulated [17] if no further edge can be added without introducing a crossing. Clearly, optimal 1-planar graphs are maximally dense, and maximally dense 1-planar graphs are maximal, but not conversely.…”
Section: Introductionmentioning
confidence: 99%
“…It can be extended to maximally dense 1-planar graphs and specialized to 5-connected optimal 1-planar graphs. Our algorithm improves upon the cubic running time algorithm of Chen et al [17], which solves a more general problem and searches 4-cycles and other types of separators. Combinatorial properties of the reductions are explored in [10].…”
A graph with n vertices is 1-planar if it can be drawn in the plane such that each edge is crossed at most once, and is optimal if it has the maximum of 4n − 8 edges. We show that optimal 1-planar graphs can be recognized in linear time. Our algorithm implements a graph reduction system with two rules, which can be used to reduce every optimal 1-planar graph to an irreducible extended wheel graph. The graph reduction system is non-deterministic, constraint, and non-confluent.
“…10a by exchanging edges ( p, s), (c, h) and ( p, h), (c, s). Consider candidate c in B 17 . Then H (c) = (2, 3, 4, 4, 4, 5, 6) violates optimal 1-planarity.…”
Section: Discussionmentioning
confidence: 99%
“…In his introductory paper on 1-planar graphs, Ringel studied the coloring problem and observed that a pair of crossing edges can be completed to K 4 by adding planar edges. 1-Planar graphs generalize 4-map graphs, which are the graphs of adjacencies of nations of a map [16,17]. Two nations are adjacent if they share a The first study of structural properties of 1-planar graphs is by Bodendiek, Schumacher, and Wagner [7,8].…”
Section: Introductionmentioning
confidence: 99%
“…A 1-planar graph G is maximally dense or maximum [36] if there is no 1-planar graph of the same size with more edges. It is maximal 1-planar if the addition of any edge destroys 1-planarity and planar-maximal or triangulated [17] if no further edge can be added without introducing a crossing. Clearly, optimal 1-planar graphs are maximally dense, and maximally dense 1-planar graphs are maximal, but not conversely.…”
Section: Introductionmentioning
confidence: 99%
“…It can be extended to maximally dense 1-planar graphs and specialized to 5-connected optimal 1-planar graphs. Our algorithm improves upon the cubic running time algorithm of Chen et al [17], which solves a more general problem and searches 4-cycles and other types of separators. Combinatorial properties of the reductions are explored in [10].…”
A graph with n vertices is 1-planar if it can be drawn in the plane such that each edge is crossed at most once, and is optimal if it has the maximum of 4n − 8 edges. We show that optimal 1-planar graphs can be recognized in linear time. Our algorithm implements a graph reduction system with two rules, which can be used to reduce every optimal 1-planar graph to an irreducible extended wheel graph. The graph reduction system is non-deterministic, constraint, and non-confluent.
“…In [31] it is shown that testing if a graph is a map graph can be done in polynomial time. However, in [9] it is argued that the exponent of the polynomial bounding its running time from above is about 120. This makes it impractical to use the algorithm in [31].…”
We present a novel paradigm to visualize the evolution of the service provided by one of the most popular root name servers, called K-root, operated by the RIPE Network Coordination Centre (RIPE NCC) and distributed in several locations (instances) worldwide. Our approach can be used to either monitor what happened during a prescribed time interval or observe the status of the service in near real-time. We visualize how and when the clients of K-root migrate from one instance to another, how the workload associated with each instance changes over time, and what are the instances that contribute to offer the service to a selected Internet Service Provider. In addition, the visualization aims at distinguishing usual from unusual operational patterns. This helps not only to improve the quality of the service but also to spot security-related issues and to investigate unexpected routing changes.
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