Some Types of Irregular Labeling of Diamond Networks on Ten Vertices

There are three interesting parameters in irregular networks based on total labelling, i.e. the total vertex irregularity strength, the total edge irregularity strength, and the total irregularity strength of a graph. Besides that, there is a parameter based on edge labelling, i.e., the irregular labelling. In this paper, we determined the four parameters for diamond graph on eight vertices.

FAST ROBUST ARITHMETICS FOR GEOMETRIC ALGORITHMS AND APPLICATIONS TO GIS

Geometric predicates are used in many GIS algorithms, such as the construction of Delaunay Triangulations for Triangulated Irregular Networks (TIN) or geospatial predicates. With floating-point arithmetic, these computations can incur roundoff errors that may lead to incorrect results and inconsistencies, causing computations to fail. This issue has been addressed using a combination of exact arithmetics for robustness and floating-point filters to mitigate the computational cost of exact computations. The implementation of exact computations and floating-point filters can be a difficult task, and code generation tools have been proposed to address this. We present a new C++ meta-programming framework for the generation of fast, robust predicates for arbitrary geometric predicates based on polynomial expressions. We show examples of how this approach produces correct results for GIS data sets that could lead to incorrect predicate results for naive implementations. We also show benchmark results that demonstrate that our implementation can compete with state-of-the-art solutions.

Recognizing Visibility Graphs of Triangulated Irregular Networks

A Triangulated Irregular Network (TIN) is a data structure that is usually used for representing and storing monotone geographic surfaces, approximately. In this representation, the surface is approximated by a set of triangular faces whose projection on the XY-plane is a triangulation. The visibility graph of a TIN is a graph whose vertices correspond to the vertices of the TIN and there is an edge between two vertices if their corresponding vertices on TIN see each other, i.e. the segment that connects these vertices completely lies above the TIN. Computing the visibility graph of a TIN and its properties have been considered thoroughly in the literature. In this paper, we consider this problem in reverse: Given a graph G, is there a TIN with the same visibility graph as G? We show that this problem is ∃ℝ-Complete.

Reliability Evaluation of Generalized Exchanged X-Cubes Based on the Condition of g-Good-Neighbor

In the cloud computing environment with massive information services and decision-making resources, the accuracy and reliability of information are more important than previous single closed systems. Therefore, ensuring the reliability of information and the stable operation of the system are the core problems in the research fields such as the Internet Plus and the Internet of Things. The connectivity and diagnosability are two important measures for the fault tolerance of multiprocessor systems. The g-good-neighbor conditional connectivity (Rg-connectivity) is the minimum number of nodes that make the graph disconnected, and each node has at least g neighbors in every remaining component. The g-good-neighbor conditional diagnosability (g-GNCD) is the maximum number of faulty processors that has been correctly identified in a system, and any fault-free processor has no less than g fault-free neighbors. Exchanged X-cubes are a class of irregular networks, obtained by deleting links from hypercubes and some variant networks of hypercubes (X-cubes). They not only combine the advantages of X-cubes but also reduce the interconnection complexity. Exchanged X-cubes classify its nodes into two different classes clusters with a unique connecting rule. In this paper, we propose the generalized exchanged X-cubes framework so that architecture can be constructed by different connecting rules. Furthermore, we study the Rg-connectivity and g-GNCD of generalized exchanged X-cubes under the PMC and MM∗ models. As applications, the Rg-connectivity and g-GNCD of generalized exchanged hypercubes, dual-cube-like networks, generalized exchanged crossed cubes, and locally generalized exchanged twisted cubes are determined, respectively.

3D Simplification Methods and Large Scale Terrain Tiling

This paper tackles the problem of generating world-scale multi-resolution triangulated irregular networks optimized for web-based visualization. Starting with a large-scale high-resolution regularly gridded terrain, we create a pyramid of triangulated irregular networks representing distinct levels of detail, where each level of detail is composed of small tiles of a fixed size. The main contribution of this paper is to redefine three different state-of-the-art 3D simplification methods to efficiently work at the tile level, thus rendering the process highly parallelizable. These modifications focus on the restriction of maintaining the vertices on the border edges of a tile that is coincident with its neighbors, at the same level of detail. We define these restrictions on the three different types of simplification algorithms (greedy insertion, edge-collapse simplification, and point set simplification); each of which imposes different assumptions on the input data. We implement at least one representative method of each type and compare both qualitatively and quantitatively on a large-scale dataset covering the European area at a resolution of 1/16 of an arc minute in the context of the European Marine Observations Data network (EMODnet) Bathymetry project. The results show that, although the simplification method designed for elevation data attains the best results in terms of mean error with respect to the original terrain, the other, more generic state-of-the-art 3D simplification techniques create a comparable error while providing different complexities for the triangle meshes.