网络拓扑的超能整循环图构造

循环图是一类重要的网络拓扑结构图,在并行计算和分布计算中发挥重要作用。图[G]的能量[E(G)]定义为图的特征值的绝对值之和。具有[n]个顶点的图[G]称为超能图如果图[G]的能量[E(G)>2n-2]。一个图称为循环图,若它是循环群上的Cayley图,即它的邻接矩阵是一个循环矩阵;整循环图是指循环图的特征值全为整数。借助Ramanujans和,利用Euler函数和Mobius函数,讨论了整循环图的超能性。利用Cartesian积图给出了一个构造超能整循环图的方法。     

Pancyclicity of recursive circulant graphs

In this paper, we study the existence of cycles of all lengths in the recursive circulant graphs, and we show a necessary and sufficient condition for the graph being pancyclic and bipancyclic.     

Dense Gaussian Networks: Suitable Topologies for On-Chip Multiprocessors

This paper explores the suitability of dense circulant graphs of degree four for the design of on-chip interconnection networks. Networks based on these graphs reduce the Torus diameter in a factor , which translates into significant performance gains for unicast traffic. In addition, they are clearly superior to Tori when managing collective communications. This paper introduces a new two-dimensional node’s labeling of the networks explored which simplifies their analysis and exploitation. In particular, it provides simple and optimal solutions to two important architectural issues: routing and broadcasting. Other implementation issues such as network folding and scalability by using hierarchical networks are also explored in this work.     

Efficient domination in circulant graphs with two chord lengths

Domination is an important property in the design of efficient computer interconnection networks. We provide a complete characterization of circulant graphs with two chord lengths that admit an efficient dominating set. In particular, for 3-regular and 4-regular circulant graphs, we give necessary and sufficient conditions for the existence of efficient dominating sets and we describe their exact structure according to the relationship between chords.     

Embedding of special classes of circulant networks,hypercubes and generalized Petersen graphs

Hypercubes are a very popular model for parallel computation because of their regularity and the relatively small number of interprocessor connections. In this paper, we present an algorithm for embedding special class of circulant networks into their optimal hypercubes with dilation 2 and prove its correctness. Also, we embed special class of circulant networks into special class of generalized Petersen graphs with dilation 2 and vice versa.     

Random Walks,Bisections and Gossiping in Circulant Graphs

Circulant graphs are regular graphs based on Cayley graphs defined on the Abelian group \(\mathbb{Z}_{n}\) . They are popular network topologies that arise in distributed computing. Using number theoretical tools, we first prove two main results for random directed k-regular circulant graphs with n vertices, when n is sufficiently large and k is fixed. First, for any fixed ε>0, n=p prime and L≥p ^1/k (logp)^1+1/k+ε , walks of length at most L terminate at every vertex with asymptotically the same probability. Second, for any n, there is a polynomial time algorithm that for almost all undirected 2r-regular circulant graphs finds a vertex bisector and an edge bisector, both of size less than n ^1?1/r+o(1). We then prove that the latter result also holds for all (rather than for almost all) 2r-regular circulant graphs with n=p, prime, vertices, while, in general, it does not hold for composite n. Using the bisection results, we provide lower bounds on the number of rounds required by any gossiping algorithms for any n. We introduce generic distributed algorithms to solve the gossip problem in any circulant graphs. We illustrate the efficiency of these algorithms by giving nearly matching upper bounds of the number of rounds required by these algorithms in the vertex-disjoint and the edge-disjoint paths communication models in particular circulant graphs.     

图神经网络在复杂图挖掘上的研究进展

图神经网络对非欧式空间数据建立了深度学习框架,相比传统网络表示学习模型,它对图结构能够实施更加深层的信息聚合操作.近年来,图神经网络完成了向复杂图结构的迁移,诞生了一系列基于复杂图的图神经网络模型.然而,现有综述文章缺乏对复杂图神经网络全面、系统的归纳和总结工作.将复杂图分为异质图、动态图和超图3种类型.将异质图神经网络按照信息聚合方式划分为关系类型感知和元路径感知两大类,在此基础上,分别介绍普通异质图和知识图谱.将动态图神经网络按照处理时序信息的方式划分成基于循环神经网络、基于自编码器以及时空图神经网络三大类.将超图神经网络按照是否将超图展开成成对图划分为展开型和非展开型两大类,进一步按照展开方式将展开型划分成星形展开、团式展开和线形展开3种类型.详细阐述了每种算法的核心思想,比较了不同算法间的优缺点,系统列举了各类复杂图神经网络的关键算法、(交叉)应用领域和常用数据集,并对未来可能的研究方向进行了展望.     

Perception of bar graphs – A biased impression?

Computers provide ubiquitous contact to data graphs. Yet, employing the power of the human perception system bears the risk of being subject to its biases. Data graphs are used to present the means of different conditions and are supposed to convey group information, such as variability across conditions, as well as the grand average. Across three samples, we tested whether there is a bias in the central tendency perceived in bar graphs, 53 participants with a mean age of 27 years (plus replication with N = 38, mean age = 23 years). Participants were provided with bar and point graphs and had to judge their means. We found that the mean value was systematically underestimated in bar graphs (but not in point graphs) across different methods of testing for biased evaluation. In a second experiment (N = 80, mean age = 24 years) we replicated and extended this finding, by testing the effect of outliers on the bias in average estimation. For instance, outliers might trigger controlled processing. Yet, the underestimation of the average was replicated and was not affected by including outliers – despite that the estimate was torn towards the outlier. Thus, we should be cautious with relying on bar graphs when a bias free estimate of the grand average is relevant.     

Wirelength of 1-fault hamiltonian graphs into wheels and fans

In this paper we obtain a fundamental result to find the exact wirelength of 1-fault hamiltonian graphs into wheels and fans. Using this result we compute the exact wirelength of circulant graphs, generalized Petersen graphs, augmented cubes, crossed cubes, M?bius cubes, locally twisted cubes, twisted cubes, twisted n-cubes, generalized twisted cubes, hierarchical cubic networks, alternating group graphs, arrangement graphs and tori into wheels and fans. In addition, we find the exact wirelength of hypercubes, folded hypercubes, shuffle cubes, cube connected cycles, cyclic-cubes, wrapped butterfly networks and star graphs into fans.     

Optimal layouts of midimew networks

Midimew networks are mesh-connected networks derived from a subset of degree-4 circulant graphs. They have minimum diameter and average distance among all degree-4 circulant graphs, and are better than some of the most common topologies for parallel computers in terms of various cost measures. Among the many midimew networks, the rectangular ones appear to be most suitable for practical implementation. Unfortunately, with the normal way of laying out these networks on a 2D plane, long cross wires that grow with the size of the network exist. In this paper, we propose ways to lay out rectangular midimew networks in a 2D grid so that the length of the longest wire is at most a small constant. We prove that these constants are optimal under the assumption that rows and columns are moved as a whole during the layout process     

Edge-colouring of join graphs

A join graph is the complete union of two arbitrary graphs. We give sufficient conditions for a join graph to be 1-factorizable. As a consequence of our results, the Hilton’s Overfull Subgraph Conjecture holds true for several subclasses of join graphs.     

Symbolic graphs for attributed graph constraints

In this paper we present a new class of graphs, called symbolic graphs, to define a new class of constraints on attributed graphs. In particular, in the first part of the paper, we study the category of symbolic graphs showing that it satisfies some properties, which are the basis for the work that we present in the second part of the paper, where we study how to reason with attributed graph constraints. More precisely, we define a set of inference rules, which are the instantiation of the inference rules defined in a previous paper, for reasoning about constraints on standard graphs, showing their soundness and (weak) completeness. Moreover, the proof of soundness and completeness is also an instantiation of the corresponding proof for standard graph constraints, using the categorical properties studied in the first part of the paper. Finally, we show that adding a new inference rule makes our system sound and strongly complete.     

On the bi-enhancement of chordal-bipartite probe graphs

Given a class C of graphs, a graph G=(V,E) is said to be a C-probe graph if there exists a stable (i.e., independent) set of vertices X⊆V and a set F of pairs of vertices of X such that the graph G^′=(V,E∪F) is in the class C. Recently, there has been increasing interest and research on a variety of C-probe graph classes, such as interval probe graphs, chordal probe graphs and chain probe graphs.In this paper we focus on chordal-bipartite probe graphs. We prove a structural result that if B is a bipartite graph with no chordless cycle of length strictly greater than 6, then B is chordal-bipartite probe if and only if a certain “enhanced” graph B^∗ is a chordal-bipartite graph. This theorem is analogous to a result on interval probe graphs in Zhang (1994) [18] and to one on chordal probe graphs in Golumbic and Lipshteyn (2004) [11].     

Single-edge monotonic sequences of graphs and linear-time algorithms for minimal completions and deletions

We study graph properties that admit an increasing, or equivalently decreasing, sequence of graphs on the same vertex set such that for any two consecutive graphs in the sequence their difference is a single edge. This is useful for characterizing and computing minimal completions and deletions of arbitrary graphs into having these properties. We prove that threshold graphs and chain graphs admit such sequences. Based on this characterization and other structural properties, we present linear-time algorithms both for computing minimal completions and deletions into threshold, chain, and bipartite graphs, and for extracting a minimal completion or deletion from a given completion or deletion. Minimum completions and deletions into these classes are NP-hard to compute.     

Efficient parallel recognition of some circular arc graphs,I

We present the first efficient parallel algorithms for recognizing some subclasses of circular arc graphs including circular arc graphs and proper interval graphs. These algorithms run in O(log² n) time withO(n ³) processors on a CRCW PRAM. An intersection representation can also be constructed within the same resource bounds. Furthermore, we propose some new characterizations of circular arc graphs and proper interval graphs.Portions of this paper have appeared in preliminary form in theProceedings of the 1989 IEEE international Symposium on Circuits and Systems [9], theProceedings of the 1989 Workshop on Algorithms and Data Structures [10], and theProceedings of the 1990 Canadian Conference on Computational Geometry [11].     

Clique-perfectness and balancedness of some graph classes

A graph is clique-perfect if the maximum size of a clique-independent set (a set of pairwise disjoint maximal cliques) and the minimum size of a clique-transversal set (a set of vertices meeting every maximal clique) coincide for each induced subgraph. A graph is balanced if its clique-matrix contains no square submatrix of odd size with exactly two ones per row and column. In this work, we give linear-time recognition algorithms and minimal forbidden induced subgraph characterizations of clique-perfectness and balancedness of P₄-tidy graphs and a linear-time algorithm for computing a maximum clique-independent set and a minimum clique-transversal set for any P₄-tidy graph. We also give a minimal forbidden induced subgraph characterization and a linear-time recognition algorithm for balancedness of paw-free graphs. Finally, we show that clique-perfectness of diamond-free graphs can be decided in polynomial time by showing that a diamond-free graph is clique-perfect if and only if it is balanced.     

Bipolar fuzzy graphs

In this paper, we introduce the notion of bipolar fuzzy graphs, describe various methods of their construction, discuss the concept of isomorphisms of these graphs, and investigate some of their important properties. We then introduce the notion of strong bipolar fuzzy graphs and study some of their properties. We also discuss some propositions of self complementary and self weak complementary strong bipolar fuzzy graphs.     

Computing the hyperbolicity constant of a cubic graph

In this paper we obtain information about the hyperbolicity constant of cubic graphs. They are a very interesting class of graphs with many applications; furthermore, they are also very important in the study of Gromov hyperbolicity, since for any graph G with bounded maximum degree there exists a cubic graph G* such that G is hyperbolic if and only if G* is hyperbolic. We find some characterizations for the cubic graphs which have small hyperbolicity constants, i.e. the graphs which are like trees (in the Gromov sense). Besides, we obtain bounds for the hyperbolicity constant of the complement graph of a cubic graph; our main result of this kind says that for any finite cubic graph G which is not isomorphic either to K₄ or to K_{3, 3}, the inequalities 5k/4≤δ (?)≤3k/2 hold, if k is the length of every edge in G.