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.     

Maximum induced subgraph of a recursive circulant

The recursive circulant RC(n²,4) enjoys several attractive topological properties. Let max_?G(m) denote the maximum number of edges in a subgraph of graph G induced by m nodes. In this paper, we show that , where p₀>p₁>?>pr are nonnegative integers defined by . We then apply this formula to find the bisection width of RC(n²,4). The conclusion shows that, as n-dimensional cube, RC(n²,4) enjoys a linear bisection width.     

Reversals Cayley graphs of symmetric groups

Corresponding to genome rearrangements by reversals, we propose a new reversal Cayley graph RSn as the Cayley graph Cay(Sn,Ωn), where Sn is the symmetric group of degree n and Ωn is the set of all reversals of Sn. Graph properties including connectivity, diameter and hamiltonicity, are investigated for this kind of graphs.     

On the partition dimension of a class of circulant graphs

For a vertex v   of a connected graph G(V,E)$G(V,E)$ and a subset S of V, the distance between a vertex v and S   is defined by d(v,S)=min{d(v,x):x∈S}$d(v,S)=\min \{d(v,x):x\in S\}$. For an ordered k  -partition π={_S1,_S2…_Sk}$\pi =\{S_1,S_2\dots S_k\}$ of V, the partition representation of v with respect to π is the k  -vector r(v|π)=(d(v,_S1),d(v,_S2)…d(v,_Sk))$r(v|\pi )=(d(v,S_1),d(v,S_2)\dots d(v,S_k))$. The k-partition π is a resolving partition if the k  -vectors r(v|π)$r(v|\pi )$, v∈V(G)$v\in V(G)$ are distinct. The minimum k for which there is a resolving k-partition of V is the partition dimension of G. Salman et al. [1] in their paper which appeared in Acta Mathematica Sinica, English Series   proved that partition dimension of a class of circulant graph G(n,±{1,2})$G(n,\pm \{1,2\})$, for all even n?6$n?6$ is four. In this paper we prove that it is three.     

On the number of spanning trees of circulant graphs

In this paper, we derive a simple formula for the number of spanning trees of the circulant graphs. Some special cases of the circulant graphs are also taken into account.     

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。     

Honeycomb toroidal graphs are Cayley graphs

There is a particular family of trivalent vertex-transitive graphs that have been called generalized honeycomb tori by some and brick products by others. They have been studied as hexagonal embeddings on the torus as well. We show that all these graphs are Cayley graphs on generalized dihedral groups.     

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.     

Edge-bipancyclicity and edge-fault-tolerant bipancyclicity of bubble-sort graphs

A bipartite graph G is bipancyclic if G has a cycle of length l for every even 4?l?|V(G)|. For a bipancyclic graph G and any edge e, G is edge-bipancyclic if e lies on a cycle of any even length l of G. In this paper, we show that the bubble-sort graph Bn is bipancyclic for n?4 and also show that it is edge-bipancyclic for n?5. Assume that F is a subset of E(Bn). We prove that Bn−F is bipancyclic, when n?4 and |F|?n−3. Since Bn is a (n−1)-regular graph, this result is optimal in the worst case.     

Conditional matching preclusion for the arrangement graphs

The matching preclusion number of a graph is the minimum number of edges whose deletion results in a graph that has neither perfect matchings nor almost-perfect matchings. For many interconnection networks, the optimal sets are precisely those induced by a single vertex. Recently, the conditional matching preclusion number of a graph was introduced to look for obstruction sets beyond those induced by a single vertex. It is defined to be the minimum number of edges whose deletion results in a graph with no isolated vertices that has neither perfect matchings nor almost-perfect matchings. In this paper we find this number and classify all optimal sets for the arrangement graphs, one of the most popular interconnection networks.     

A note about some properties of BC graphs

BC graphs is an important class of hypercube-like interconnection networks. In this paper, some properties—vertex-pancyclicity, super-connectivity and the maximum number of edges joining vertices are studied.     

Linear election in pancake graphs

Pancake graphs have been proposed as an attractive alternative to hypercube networks. They have a smaller diameter and a lower degree. They also have a hierarchical structure which can be exploited in designing algorithms.In this paper, we propose a leader election algorithm for oriented pancake graphs. The algorithm has a message complexity that is linear in the order of the graph.     

The (strong) rainbow connection numbers of Cayley graphs on Abelian groups

A path in an edge-colored graph G, whose adjacent edges may have the same color, is called a rainbow path if no two edges of the path are colored the same. The rainbow connection number rc(G) of G is the minimum integer i for which there exists an i-edge-coloring of G such that every two distinct vertices of G are connected by a rainbow path. The strong rainbow connection number src(G) of G is the minimum integer i for which there exists an i-edge-coloring of G such that every two distinct vertices u and v of G are connected by a rainbow path of length d(u,v). In this paper, we give upper and lower bounds of the (strong) rainbow connection numbers of Cayley graphs on Abelian groups. Moreover, we determine the (strong) rainbow connection numbers of some special cases.     

Fault diameter of Cartesian product graphs

The (k−1)-fault diameter Dk(G) of a k-connected graph G is the maximum diameter of G−F for any F⊂V(G) with |F|<k. Krishnamoorthy and Krishnamurthy first proposed this concept and gave Dκ(G₁)+κ(G₂)(G₁×G₂)?Dκ(G₁)(G₁)+Dκ(G₂)(G₂) when κ(G₁×G₂)=κ(G₁)+κ(G₂), where κ(G) is the connectivity of G. This paper gives a counterexample to this bound and establishes Dk₁+k₂(G₁×G₂)?Dk₁(G₁)+Dk₂(G₂)+1 for any ki-connected graph Gi and ki?1 for i=1,2.     

The pessimistic diagnosability of alternating group graphs under the PMC model

The process of identifying faulty processors is called the diagnosis of the system. Several diagnostic models have been proposed, the most popular is the PMC (Preparata, Metze and Chen) diagnostic model. The pessimistic diagnosis strategy is a classic strategy based on the PMC model in which isolates all faulty nodes within a set containing at most one fault-free node. A system is t/t$t/t$-diagnosable if, provided the number of faulty processors is bounded by t, all faulty processors can be isolated within a set of size at most t with at most one fault-free node mistaken as a faulty one. The pessimistic diagnosability of a system G  , denoted by _tp(G)$t_p(G)$, is the maximal number of faulty processors so that the system G   is t/t$t/t$-diagnosable. Jwo et al. [11] introduced the alternating group graph as an interconnection network topology for computing systems. The proposed graph has many advantages over hypercubes and star graphs. For example, for all alternating group graphs, every pair of vertices in the graph are connected by a Hamiltonian path and the graph can embed cycles with arbitrary length with dilation 1. In this article, we completely determine the pessimistic diagnosability of an n  -dimensional alternating group graph, denoted by _AGn${\mathit{AG}}_n$. Furthermore, _tp(_AGn)=4n−11$t_p({\mathit{AG}}_n)=4n-11$ for n≥4$n\ge 4$.     

基于循环核矩阵的自适应目标跟踪算法

针对现在存在的基于分类的目标跟踪算法难以实现自适应目标大小变化的问题,提出并实现了基于循环核矩阵的自适应目标跟踪算法。算法首先在包含目标的感兴趣区域内采集所有的训练样本以构成一个循环矩阵结构,再使用高斯核函数构造出循环核矩阵,最后通过基于循环核矩阵的分类器的封闭形式的解进行训练和检测。同时,将比较成熟的循环矩阵理论与傅里叶分析建立连接,从而实现了在快速傅里叶变换下进行快速学习和检测。在此基础上,通过分类器对目标响应度的变化,实现自适应目标大小的变化。与一些经典的和较新的自适应目标跟踪算法进行比较,实验结果表明该算法在一定场景下能够更加准确和有效地表达目标的变化。     

Diagnosability of star graphs under the comparison diagnosis model

In this paper, the diagnosability of n-dimensional star graph Sn under the comparison diagnosis model has been studied. It is proved that Sn is (n−1)-diagnosable under the comparison diagnosis model when n?4.     

Comparing columnar,row and array DBMSs to process recursive queries on graphs

Analyzing graphs is a fundamental problem in big data analytics, for which DBMS technology does not seem competitive. On the other hand, SQL recursive queries are a fundamental mechanism to analyze graphs in a DBMS, whose processing and optimization are significantly harder than traditional SPJ queries. Columnar DBMSs are a new faster class of database system, with significantly different storage and query processing mechanisms compared to row DBMSs, still the dominating technology. With that motivation in mind, we study the optimization of recursive queries on a columnar DBMS focusing on two fundamental and complementary graph problems: transitive closure and adjacency matrix multiplication. From a query processing perspective we consider the three fundamental relational operators: selection, projection and join (SPJ), where projection subsumes SQL group-by aggregation. We present comprehensive experiments comparing recursive query processing on columnar, row and array DBMSs to analyze large graphs with different shape and density. We study the relative impact of query optimizations and we compare raw speed of DBMSs to evaluate recursive queries on graphs. Results confirm classical query optimizations that keep working well in a columnar DBMS, but their relative impact is different. Most importantly, a columnar DBMS with tuned query optimization is uniformly faster than row and array systems to analyze large graphs, regardless of their shape, density and connectivity. On the other hand, there is no clear winner between the row and array DBMSs.     

Conditional connectivity of Cayley graphs generated by transposition trees

Given a graph G and a non-negative integer h, the Rh-(edge)connectivity of G is the minimum cardinality of a set of (edges)vertices of G, if any, whose deletion disconnects G, and every remaining component has minimum degree at least h. Similarly, given a non-negative integer g, the g-(edge)extraconnectivity of G is the minimum cardinality of a set of (edges)vertices of G, if any, whose deletion disconnects G, and every remaining component has more than g vertices. In this paper, we determine R₂-(edge)connectivity and 2-extra(edge)connectivity of Cayley graphs generated by transposition trees.