Convergent drawing for mutually connected directed graphs

Directed graphs are used to represent a variety of datasets, including friendship on social networking services (SNS), pathways of genes, and citations of research papers. Graph drawing is useful in representing such datasets. At the international conference on Information Visualization (IV), we have presented a convergent edge drawing and a node layout technique for tightly and mutually connected directed graphs. The edge drawing technique in the IV paper includes three features: ordinary bundling of edges connecting pairs of node clusters, convergence of multiple bundles that connect to the same node cluster, and shape adjustment of two bundles connecting the same pair of node clusters. In this paper, we present improved node layout and edge drawing techniques, which make our edge bundling more effective. This paper also introduces a case study with a directed paper citation graph dataset.vvvvv     

基于遗传算法的有向无环图画图算法

在研究了现有画有向无环图的主要方法的基础上提出一种基于遗传算法的有向无环图画图算法,将一般有向无环图的画图问题转换为函数优化问题,用遗传算法求目标函数最优解的近似值。实验表明此算法具有算法统一、方法简单、容易实现、易于修改,并且具有自适应、自学习和易于并行化的特点。     

A browser for directed graphs

A general-purpose browser for directed graphs is described. The browser provides operations to examine and edit graphs and to generate a layout for a graph automatically that minimizes edge crossings. Two layout algorithms were implemented. A hierarchical graph layout algorithm was found to be best for directed graphs. The graph browser also has facilities that allow it to be integrated with other applications (e.g. a program browser). These facilities and our experiences building a program call-graph browser are described.     

An algorithm for drawing planar graphs

A simple algorithm for drawing 3‐connected planar graphs is presented. It is derived from the Fruchterman and Reingold spring embedding algorithm by deleting all repulsive forces and fixing vertices of an outer face. The algorithm is implemented in the system for manipulating discrete mathematical structures Vega. Some examples of derived figures are given. Copyright © 1999 John Wiley & Sons, Ltd.     

A note on leader election in directed split-stars and directed alternating group graphs

A leader node is defined to be any node of the network unambiguously identified by some characteristics. In this paper, we first present a distributed algorithm for finding a leader node of a directed split-star. Moreover, an efficient self-stabilizing leader election algorithm that converges with linear rounds is proposed for directed split-stars. Actually, the distributed algorithm and the self-stabilizing algorithm are also applicable to the problem of directed alternating group graphs. As far as we know, no self-stabilizing leader election algorithm was known for the two graphs.     

Optimization of hierarchical directed graphs

A machine- and language-independent representation for programs suitable for use within a compiler is presented. This representation is the hierarchical directed graph. Powerful code optimization techniques are presented in the context of this representation. An experimental optimizer has been built to validate the ideas discussed. The power of the representation is evident in the compactness of the code implementing the optimizations.     

Dominating sets in directed graphs

We consider the problem of incrementally computing a minimal dominating set of a directed graph after the insertion or deletion of a set of arcs. Earlier results have either focused on the study of the properties that minimum (not minimal) dominating sets preserved or lacked to investigate which update affects a minimal dominating set and in what ways. In this paper, we first show how to incrementally compute a minimal dominating set on arc insertions. We then reduce the case of computing a minimal dominating set on arc deletions to the case of insertions. Some properties on minimal dominating sets are provided to support the incremental strategy. Lastly, we give a new bound on the size of minimum dominating sets based on those results.     

A space-filling visualization technique for multivariate small-world graphs

We introduce an information visualization technique, known as GreenCurve, for large multivariate sparse graphs that exhibit small-world properties. Our fractal-based design approach uses spatial cues to approximate the node connections and thus eliminates the links between the nodes in the visualization. The paper describes a robust algorithm to order the neighboring nodes of a large sparse graph by solving the Fiedler vector of its graph Laplacian, and then fold the graph nodes into a space-filling fractal curve based on the Fiedler vector. The result is a highly compact visualization that gives a succinct overview of the graph with guaranteed visibility of every graph node. GreenCurve is designed with the power grid infrastructure in mind. It is intended for use in conjunction with other visualization techniques to support electric power grid operations. The research and development of GreenCurve was conducted in collaboration with domain experts who understand the challenges and possibilities intrinsic to the power grid infrastructure. The paper reports a case study on applying GreenCurve to a power grid problem and presents a usability study to evaluate the design claims that we set forth.     

Gaussian conditional random fields extended for directed graphs

For many real-world applications, structured regression is commonly used for predicting output variables that have some internal structure. Gaussian conditional random fields (GCRF) are a widely used type of structured regression model that incorporates the outputs of unstructured predictors and the correlation between objects in order to achieve higher accuracy. However, applications of this model are limited to objects that are symmetrically correlated, while interaction between objects is asymmetric in many cases. In this work we propose a new model, called Directed Gaussian conditional random fields (DirGCRF), which extends GCRF to allow modeling asymmetric relationships (e.g. friendship, influence, love, solidarity, etc.). The DirGCRF models the response variable as a function of both the outputs of unstructured predictors and the asymmetric structure. The effectiveness of the proposed model is characterized on six types of synthetic datasets and four real-world applications where DirGCRF was consistently more accurate than the standard GCRF model and baseline unstructured models.     

Combinatorial algorithms for feedback problems in directed graphs

Given a weighted directed graph G=(V,A), the minimum feedback arc set problem consists of finding a minimum weight set of arcs A′⊆A such that the directed graph (V,A?A′) is acyclic. Similarly, the minimum feedback vertex set problem consists of finding a minimum weight set of vertices containing at least one vertex for each directed cycle. Both problems are NP-complete. We present simple combinatorial algorithms for these problems that achieve an approximation ratio bounded by the length, in terms of number of arcs, of a longest simple cycle of the digraph.     

权长相合的带权无向图画图算法

针对带权无向图的输出需用边长反映权值大小的问题,提出了一种基于遗传算法的带权无向图画图算法,通过对顶点坐标的编码进行交叉和变异来得到理想的节点坐标,变异算子结合了非一致性变异和单点邻域变异,并在适应度函数中运用顶点平均距离、边交叉数、多度顶点相关边夹角均匀度、边的权值长度比一致程度四个美学标准。实验结果表明,该算法画出的图形连线无交叉,分支清晰,权值—长度相合,能得到清晰、美观且能直观反映权值的可视化输出结果,可应用于带权无向图的可视化输出系统的设计。     

Efficient parallel algorithms for path problems in directed graphs

In this paper we describe a technique for finding efficient parallel algorithms for problems on directed graphs that involve checking the existence of certain kinds of paths in the graph. This technique provides efficient algorithms for finding dominators in flow graphs, performing interval and loop analysis on reducible flow graphs, and finding the feedback vertices of a digraph. Each of these algorithms takesO(log² n) time using the same number of processors needed for fast matrix multiplication. All of these bounds are for an EREW PRAM.     

Parallel algorithms for minimal spanning trees of directed graphs

The main results of this paper are efficient parallel algorithms, MSP and LOCATE, for computing minimal spanning trees and locating minimal paths in directed graphs, respectively. Algorithm MSP has time complexityO(log³ n) usingO(n ³/logn) processors, while LOCATE has time complexityO(logn) usingO(n ²) processors. Algorithm MSP is derived from sequential algorithms, when the unbounded parallelism model is used.     

On a game in directed graphs

Inspired by recent algorithms for electing a leader in a distributed system, we study the following game in a directed graph: each vertex selects one of its outgoing arcs (if any) and eliminates the other endpoint of this arc; the remaining vertices play on until no arcs remain. We call a directed graph lethal if the game must end with all vertices eliminated and mortal if it is possible that the game ends with all vertices eliminated. We show that lethal graphs are precisely collections of vertex-disjoint cycles, and that the problem of deciding whether or not a given directed graph is mortal is NP-complete (and hence it is likely that no “nice” characterization of mortal graphs exists).     

利用遗传算法改进DAG绘制的方法

DAG图（Directed Acyclic Graph）广泛应用于数据库建模、工程设计等领域。DAG图一般用矩阵来存储,能够将矩阵存储的DAG图正确、美观地画出来,使得DAG图更直观,清晰,方便各种问题的分析和处理。DAG图的绘制包含分层、最小化边交叉数和删除哑结点。提出了基于遗传算法的分层和最小化边交叉数的方法和删除哑结点的启发式算法。实例结果表明提出的方法能有效解决DAG图绘制中的交叉点问题。     

Efficient parallel algorithms for path problems in directed graphs

In this paper we describe a technique for finding efficient parallel algorithms for problems on directed graphs that involve checking the existence of certain kinds of paths in the graph. This technique provides efficient algorithms for finding dominators in flow graphs, performing interval and loop analysis on reducible flow graphs, and finding the feedback vertices of a digraph. Each of these algorithms takesO(log² n) time using the same number of processors needed for fast matrix multiplication. All of these bounds are for an EREW PRAM.