On the edge-tenacity of the middle graph of a graph

We consider the problem of efficiently breaking a graph into small components by removing edges. One measure of how easily this can be done is the edge-tenacity. Given a set of edges of G, the score of S is defined as sc(S)=[| S|+τ (G?S)]/[w(G?S)]. Formally, the edge-tenacity of a graph G is defined as T′(G)=min sc(S), where the minimum is taken over all edge-sets S of G. A subset S of E(G) is said to be a T′-set of G if T′(G)=sc(S). Note that if G is disconnected, the set S may be empty. For any graph G, τ(G?S) is the number of vertices in the largest component of G?S and w(G?S) is the number of components of G?S. The middle graph M(G) of a graph G is the graph obtained from G by inserting a new vertex into every edge of G and by joining by edges those pairs of these new vertices which lie on adjacent edges of G. In this paper, we give the edge-tenacity of the middle graph of specific families of graphs and its relationships with other parameters.     

Independence and k-domination in graphs

A subset S of vertices of a graph G is k-dominating if every vertex not in S has at least k neighbours in S. The k-domination number γ _k (G) is the minimum cardinality of a k-dominating set of G, and α(G) denotes the cardinality of a maximum independent set of G. Brook's well-known bound for the chromatic number χ and the inequality α(G)≥n(G)/χ(G) for a graph G imply that α(G)≥n(G)/Δ(G) when G is non-regular and α(G)≥n(G)/(Δ(G)+1) otherwise. In this paper, we present a new proof of this property and derive some bounds on γ _k (G). In particular, we show that, if G is connected with δ(G)≥k then γ _k (G)≤(Δ(G)?1)α(G) with the exception of G being a cycle of odd length or the complete graph of order k+1. Finally, we characterize the connected non-regular graphs G satisfying equality in these bounds and present a conjecture for the regular case.     

Constructing a Tree from Homeomorphic Subtrees, with Applications to Computational Evolutionary Biology

This paper discusses how to count and generate strings that are ``distinct' in two senses: p -distinct and b -distinct. Two strings x on alphabet A and x' on alphabet A' are said to be p -distinct iff they represent distinct ``patterns'; that is, iff there exists no one—one mapping from A to A' that transforms x into x' . Thus aab and baa are p -distinct while aab and ddc are p -equivalent. On the other hand, x and x' are said to be b -distinct iff they give rise to distinct border (failure function) arrays: thus aab with border array 010 is b -distinct from aba with border array 001 . The number of p -distinct (resp. b -distinct) strings of length n formed using exactly k different letters is the [k,n] entry in an infinite p' (resp. b' ) array. Column sums p[n] and b[n] in these arrays give the number of distinct strings of length n . We present algorithms to compute, in constant time per string, all p -distinct (resp. b -distinct) strings of length n formed using exactly k letters, and we also show how to compute all elements p'[k,n] and b'[k,n] . These ideas and results have application to the efficient generation of appropriate test data sets for many string algorithms. Received December 21, 1995; revised April 28, 1997.     

Worst-case optimal algorithm for XPath evaluation over XML streams

We consider the XPath evaluation problem: Evaluate an XPath query Q on a streaming XML document D; i.e., determine the set Q(D) of document elements selected by Q. We mainly consider Conjunctive XPath queries that involve only the child and descendant axes. Previously known in-memory algorithms for this problem use O(|D|) space and O(|Q||D|) time. Several previously known algorithms for the streaming version use Ω(dn) space and Ω(dn|D|) time in the worst case; d denotes the depth of D, and n denotes the number of location steps in Q. Their exponential space requirement could well exceed the O(|D|) space used by the in-memory algorithms. We present an efficient algorithm that uses O(d|Q|+nc) space and O((|Q|+dn)|D|) time in the worst case; c denotes the maximum number of elements of D that can be candidates for output, at any one instant. For some worst case Q and D, the memory space used by our algorithm matches our lower bound proved in a different paper; so, our algorithm uses optimal memory space in the worst case.     

A class of hybrid collocation methods for third-order ordinary differential equations

A class of numerical methods is proposed for solving general third-order ordinary differential equations directly by collocation at the grid points x = x _n+j , i = 0(1)k and at an off grid point x = x _n+u , where k is the step number of the method and u is an arbitrary rational number in (x _n , x _n+k ). A predictor of order 2k ? 1 is also proposed to cater for y _n+k in the main method. Taylor series expansion is employed for the calculation of y _n+1, y _n+2, y _n+u and their higher derivatives. Evaluation of the resulting method at x = x _n+k for any value of u in the specified open interval yields a particular discrete scheme as a special case of the method. The efficiency of the method is tested on some general initial value problems of third-order ordinary differential equations.     

The construction of mutually independent Hamiltonian cycles in bubble-sort graphs

A Hamiltonian cycle C=? u ₁, u ₂, …, u _n(G), u ₁ ? with n(G)=number of vertices of G, is a cycle C(u ₁; G), where u ₁ is the beginning and ending vertex and u _i is the ith vertex in C and u _i ≠u _j for any i≠j, 1≤i, j≤n(G). A set of Hamiltonian cycles {C ₁, C ₂, …, C _k } of G is mutually independent if any two different Hamiltonian cycles are independent. For a hamiltonian graph G, the mutually independent Hamiltonianicity number of G, denoted by h(G), is the maximum integer k such that for any vertex u of G there exist k-mutually independent Hamiltonian cycles of G starting at u. In this paper, we prove that h(B _n )=n?1 if n≥4, where B _n is the n-dimensional bubble-sort graph.     

Algorithms for (0, 1, d)-graphs with d constrains

Let G be a graph with vertex set V(G). Let n, k, d be non-negative integers such that n+2k+d≤|V(G)|?2 and |V(G)|?n?d are even. A matching which saturates exactly |V(G)|?d vertices is called a defect-d matching of G. If when deleting any n vertices the remaining subgraph contains a matching of k edges and every k-matching can be extended to a defect-d matching, then G is said to be an (n, k, d)-graph. We present an algorithm to determine (0, 1, d)-graphs with d constraints. Moreover, we solve the problem of augmenting a bipartite graph G=(B, W) to be a (0, 1, d)-graph by adding fewest edges, where d=∥B|?|W∥. The latter problem is applicable to the job assignment problem, where the number of jobs does not equal the number of persons.     

Exponential stability in mean square of neutral stochastic differential functional equations

The aim of this paper is to investigate the exponential stability in mean square for a neutral stochastic differential functional equation of the form d[x(t) − G(x_t)] = [f(t,x(t)) + g(t, x_t)]dt + σ(t, x_t)dw(t), where x_t = {x(t + s): − τ s 0}, with τ > 0, is the past history of the solution. Several interesting examples are a given for illustration.     

On the 1-fault hamiltonicity for graphs satisfying Ore's theorem and its generalization

Consider any undirected and simple graph G=(V, E), where V and E denote the vertex set and the edge set of G, respectively. Let |G|=|V|=n. The well-known Ore's theorem states that if deg_G(u)+deg_G(v)≥n+k holds for each pair of nonadjacent vertices u and v of G, then G is traceable for k=?1, hamiltonian for k=0, and hamiltonian-connected for k=1. Lin et al. generalized Ore's theorem and showed that under the same condition as above, G is r*-connected for 1≤r≤k+2 with k≥1. In this paper, we improve both theorems by showing that the hamiltonicity or r*-connectivity of any graph G satisfying the condition deg_G(u)+deg_G(v)≥n+k with k≥?1 is preserved even after one vertex or one edge is removed, unless G belongs to two exceptional families.     

On the locatic number of graphs

A vertex v of a connected graph G distinguishes a pair u, w of vertices of G if d(v, u)≠d(v, w), where d(·,·) denotes the length of a shortest path between two vertices in G. A k-partition Π={S ₁, S ₂, …, S _k } of the vertex set of G is said to be a locatic partition if for every pair of distinct vertices v and w of G, there exists a vertex s∈S _i for all 1≤i≤k that distinguishes v and w. The cardinality of a largest locatic partition is called the locatic number of G. In this paper, we study the locatic number of paths, cycles and characterize all the connected graphs of order n having locatic number n, n?1 and n?2. Some realizable results are also given in this paper.     

Centralities of a network and its line graph: an analytical comparison by means of their irregularity

Given a network G, it is known that the Bonacich centrality of the bipartite graph B(G) associated with G can be obtained in terms of the centralities of the line graph L(G) associated with G and the centrality of the network G+gr (whose adjacency matrix is obtained by adding to the adjacency matrix A(G) the diagonal matrix D=b_ij, where b_ii is the degree of node i in G) and conversely. In this contribution, we use the centrality of G to estimate the centrality of G+gr and show that the error committed is bounded by some measure of the irregularity of G. This estimate gives an analytical comparison of the eigenvector centrality of G with the centrality of L(G) in terms of some irregularity measure of G.     

Improving the panconnectedness property of locally twisted cubes

The n-dimensional locally twisted cube LTQ_n is a promising alternative to the hypercube because of its great properties. Not only is LTQ_n n-connected, but also meshes, torus, and edge-disjoint Hamiltonian cycles can embed in it. Ma and Xu [Panconnectivity of locally twisted cubes, Appl. Math. Lett. 19 (2006), pp. 681–685] investigated the panconnectivity of LTQ_n for flexible routing. In this paper, we combine panconnectivity with Hamiltonian connectedness to define Hamiltonian r-panconnectedness: a graph G of m vertices, m≥3, is Hamiltonian r-panconnected if for any three distinct vertices x, y, and z of G there exists a Hamiltonian path P of G such that P(1)=x, P(l+1)=y, and P(m)=z for every r≤l≤m?1?r, where P(i) denotes the ith vertex of P for 1≤i≤m. Then, we show that LTQ_n is Hamiltonian n-panconnected for n≥5. This property admits the path embedding via an intermediate node at any prescribed position, and our result achieves an improvement over that of Ma and Xu.     

Solving shortest paths efficiently on nearly acyclic directed graphs

Shortest path problems can be solved very efficiently when a directed graph is nearly acyclic. Earlier results defined a graph decomposition, now called the 1-dominator set, which consists of a unique collection of acyclic structures with each single acyclic structure dominated by a single associated trigger vertex. In this framework, a specialised shortest path algorithm only spends delete-min operations on trigger vertices, thereby making the computation of shortest paths through non-trigger vertices easier. A previously presented algorithm computed the 1-dominator set in O(mn) worst-case time, which allowed it to be integrated as part of an O(mn+nrlogr) time all-pairs algorithm. Here m and n respectively denote the number of edges and vertices in the graph, while r denotes the number of trigger vertices. A new algorithm presented in this paper computes the 1-dominator set in just O(m) time. This can be integrated as part of the O(m+rlogr) time spent solving single-source, improving on the value of r obtained by the earlier tree-decomposition single-source algorithm. In addition, a new bidirectional form of 1-dominator set is presented, which further improves the value of r by defining acyclic structures in both directions over edges in the graph. The bidirectional 1-dominator set can similarly be computed in O(m) time and included as part of the O(m+rlogr) time spent computing single-source. This paper also presents a new all-pairs algorithm under the more general framework where r is defined as the size of any predetermined feedback vertex set of the graph, improving the previous all-pairs time complexity from O(mn+nr²) to O(mn+r³).     

The Swap Edges of a Multiple-Sources Routing Tree

Let T be a spanning tree of a graph G and S⊂V(G) be a set of sources. The routing cost of T is the total distance from all sources to all vertices. For an edge e of T, the swap edge of e is the edge f minimizing the routing cost of the tree formed by replacing e with f. Given an undirected graph G and a spanning tree T of G, we investigate the problem of finding the swap edge for every tree edge. In this paper, we propose an O(mlog n+n ²)-time algorithm for the case of two sources and an O(mn)-time algorithm for the case of more than two sources, where m and n are the numbers of edges and vertices of G, respectively.     

Embedding of Cycles in Twisted Cubes with Edge-Pancyclic

In this paper, we study the embedding of cycles in twisted cubes. It has been proven in the literature that, for any integer l, 4≤l≤2 ⁿ , a cycle of length l can be embedded with dilation 1 in an n-dimensional twisted cube, n≥3. We obtain a stronger result of embedding of cycles with edge-pancyclic. We prove that, for any integer l, 4≤l≤2 ⁿ , and a given edge (x,y) in an n-dimensional twisted cube, n≥3, a cycle C of length l can be embedded with dilation 1 in the n-dimensional twisted cube such that (x,y) is in C in the twisted cube. Based on the proof of the edge-pancyclicity of twisted cubes, we further provide an O(llog l+n ²+nl) algorithm to find a cycle C of length l that contains (u,v) in TQ _n for any (u,v)∈E(TQ _n ) and any integer l with 4≤l≤2 ⁿ .     

Network Design with Edge-Connectivity and Degree Constraints

We consider the following network design problem; Given a vertex set V with a metric cost c on V, an integer k≥1, and a degree specification b, find a minimum cost k-edge-connected multigraph on V under the constraint that the degree of each vertex v∈V is equal to b(v). This problem generalizes metric TSP. In this paper, we show that the problem admits a ρ-approximation algorithm if b(v)≥2, v∈V, where ρ=2.5 if k is even, and ρ=2.5+1.5/k if k is odd. We also prove that the digraph version of this problem admits a 2.5-approximation algorithm and discuss some generalization of metric TSP.     

An efficient alignment algorithm for masked sequences

We consider the alignment problem where sequences may have masked regions. The bases in masked regions are either unspecified or unknown, and they will be denoted by N. We present an efficient algorithm that finds an optimal local alignment by skipping such masked regions of sequences. Our algorithm works for both the affine gap penalty model and the linear gap penalty model. The time complexity of our algorithm is O((n−T)(m−S)+vm+wn) time, where n and m are the lengths of given sequences A and B, T and S are the numbers of base N in A and B, and v and w are the numbers of masked regions in A and B, respectively.     

Stochastic adaptive pole-zero assignment with convergence analysis

The adaptive control u_n is designed for the stochastic system A(z)y_n+1 = B(z)u_n+C(z)w_n+1 with unknown constant matrix coefficients in the polynomials A(z), B(z) and C(z) in the shift-back operator with the purposes that (1) the unknown matrices are strongly consistently estimated and (2) the poles and zeros are replaced in such a way that the system itself is transferred to A⁰(z)y_n+1 = B⁰(z)u_n⁰+_n+1 with given A⁰(z), B⁰(z) and u_n⁰ so that the pole-zero assignment error {_n+1} is minimized. The problem of adaptive pole-zero assignment combined with tracking is also considered in this paper. Conditions used are imposed only on A(z), B(z) and C(z).     

A Simplified Õ(nm) Time Edge-Splitting Algorithm in Undirected Graphs

Let G=(V,E) be a multigraph which has a designated vertex s ∈ V with an even degree. For two edges e ₁ = (s,u ₁ ) and e ₂ = (s,u ₂ ) , we say that a multigraph G' is obtained from G by splitting e ₁ and e ₂ at s if two edges e ₁ and e ₂ are replaced with a single edge (u ₁ ,u ₂ ) . It is known that all edges incident to s can be split without losing the edge-connectivity of G in V-s . This complete splitting plays an important role in solving many graph connectivity problems. The currently fastest algorithm for a complete splitting [14] runs in O(n(m+n log n) log n) time, where n = |V| and m is the number of pairs of vertices between which G has an edge. Their algorithm is first designed for Eulerian multigraphs, and then extended for general multigraphs. Although the part for Eulerian multigraphs is simple, the rest for general multigraphs is considerably complicated. This paper proposes a much simpler O(n(m+n log n) log n) time algorithm for finding a complete splitting. A new edge-splitting theorem derived from our algorithm is also presented. Received March 13, 1997; revised October 10, 1997.