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A disjoint path cover of a graph is a set of pairwise vertex-disjoint paths that altogether cover every vertex of the graph. In this paper, we prove that given k sources, s 1 , …, s k , in an m -dimensional restricted hypercube-like graph with a set F of faults (vertices and/or edges), associated with k positive integers, l 1 , …, l k , whose sum is equal to the number of fault-free vertices, there exists a disjoint path cover composed of k fault-free paths, each of whose paths starts at s i and contains l i vertices for i ∈ { 1 , … , k } , provided | F | + k ≤ m − 1 . The bound, m − 1 , on | F | + k is the best possible.

The channel assignment problem (CAP) which finds an efficient assignment of channels to the transmitters of a wireless network is applicable to cellular mobile system (CMS). There are lots of results on CAP for CMS where the channel separation constraint is represented by a symmetric matrix or a graph. In particular, the Philadelphia instances and the 49-cell system are benchmark CAP for CMS and are treated in many papers. The distance multi-labelling (DM) problem on a graph with weighted vertices is an effective mathematical model of CAP for CMS in which a CMS is represented by a graph with weighted vertices, where a vertex corresponds to a cell with the number of calls on it as its weight. A DM on a graph with weighted vertices is an assignment of a set of non-negative numbers to each vertex. These numbers, which are called labels, represent the channels assigned to the demand calls in each cell. DM is a generalisation of both distance labelling and graph multi-colouring. In this study, the author introduce a new method called the layering method to find a DM on a graph with weighted vertices. Using this method, we obtain optimal DM for two Philadelphia instances. For each of them, the authors obtain a DM according to the range of separation conditions, and it includes known optimal results which are individually obtained under one separation condition.

A Hamilton -cycle in a k-uniform hypergraph of n-vertex is an ordering of all vertices, combined with an ordered subset C of edges, such that any two consecutive edges share exactly vertices and each edge in C contains k consecutive vertices.A classic result of O. Ore in 1960 is that if the degree sum of any two independent vertices in an n-vertex graph is at least n, then the graph contains a Hamiltonian cycle. Naturally, we consider to generalize it to hypergraphs situation. In this paper, we prove the following theorems. (i) For any n4k2, there is an n-vertex k-uniform hypergraph, with degree sum of any two strongly independent sets of k1 vertices bigger than 2n4(k1), contains no Hamilton l-cycle, 1k1. (ii) If the degree sum of two weakly independent sets of k1 vertices in an n-vertex k-uniform hypergraph is (1+o(1))n, then the hypergraph contains a Hamilton (k1)-cycle, where two distinct sets of k1 vertices are weakly (strongly) independent if there exist no edge containing the union of them (intersecting both of them).

We analyse the size of an independent set in a random graph on $n$ vertices with specified vertex degrees, constructed via a simple greedy algorithm: order the vertices arbitrarily, and, for each vertex in turn, place it in the independent set unless it is adjacent to some vertex already chosen. We find the limit of the expected proportion of vertices in the greedy independent set as $n \to \infty$, expressed as an integral whose upper limit is defined implicitly, valid whenever the second moment of a random vertex degree is uniformly bounded. We further show that the random proportion of vertices in the independent set converges to the jamming constant as $n \to \infty$. The results hold under weaker assumptions in a random multigraph with given degrees constructed via the configuration model., Comment: 25 pages

The maximum independent set problem is one of the most important problems in theoretical analysis on time and space complexities of exact algorithms. Theoretical improvement on upper bounds on time complexity to solve this problem in low-degree graphs can lead to an improvement on that to the problem in general graphs. In this paper, we derive an upper bound $$O^*(1.1376^n)$$ on the time complexity of a polynomial-space algorithm that solves the maximum independent set problem in an n-vertex graph with degree bounded by 4, improving all previous upper bounds on the time complexity of exact algorithms to this problem. Our algorithm is a branch-and-reduce algorithm and analyzed by using the measure-and-conquer method. To make an amortized analysis of the running time bound, we use an idea of “shift” to save some decrease of the measure from good branches to bad branches. Our algorithm first deals with small vertex cuts and vertices of degree $${\ge }5$$ , which may be created in our algorithm even if the input graph has maximum degree 4, then eliminates cycles of length 3 and 4 containing degree-4 vertices, and finally branches on degree-4 vertices. We invoke an exact algorithm for this problem in graphs with maximum degree 3 directly when the graph has no vertices of degree $${\ge }4$$ . Branching on degree-4 vertices on special local structures will be the bottleneck case, and we carefully design rules of choosing degree-4 vertices to branch on so that the resulting instances after branching decrease the measure effectively in the next step.

The resistance distance between any two vertices of a graph G is defined as the effective resistance between them if each edge of G is replaced by a unit resistor. The Kirchhoff index Kf(G) is the sum of the resistance distances between all the pairs of vertices in G. The vertex bipartiteness vb of a graph G is the minimum number of vertices whose deletion from G results in a bipartite graph. In this paper, we characterize the graph having the minimum Kf(G) values among graphs with a fixed number n of vertices and fixed vertex bipartiteness, 1 ź v b ź n - 3 .

A set of vertices S is a resolving set in a graph if each vertex has a unique array of distances to the vertices of S. The natural problem of finding the smallest cardinality of a resolving set in a graph has been widely studied over the years. In this paper, we wish to resolve a set of vertices (up to ź vertices) instead of just one vertex with the aid of the array of distances. The smallest cardinality of a set S resolving at most ź vertices is called ź-set-metric dimension. We study the problem of the ź-set-metric dimension in two infinite classes of graphs, namely, the two dimensional grid graphs and the n-dimensional binary hypercubes. We introduce a way to locate several intruders instead of only one of a resolving set.This prevents mistakes in the location procedure, see Example 2(i).New geometric approach compared to the usual resolving sets (Section 2).We give the complete and optimal results for the two dimensional grid graphs.Optimal results for a very high number of intruders in binary hypercubes.

An assignment of weights to the edges and the vertices of a graph is a vertex-coloring total weighting if adjacent vertices have different total weight sums. Of interest in this paper are vertex-coloring total weightings with weight set of cardinality two, a problem motivated by the conjecture that every graph has such a weighting using the weights 1 and 2. Here we prove the existence of such weightings for certain families of graphs using any two different real weights. A related problem where all vertices have unique weight sums is also discussed.

The hyper-Wiener index WW(G) is defined as with the summation going over all pairs of vertices in G. In this paper, we determine graphs with the minimum hyper-Wiener index among all the unicyclic graphs with n vertices and k pendent vertices.

For any integer k3, we consider the following decision problem. Given a simple graph, does there exist a partition of its vertices into two disjoint sets such that every simple k-cycle of G contains vertices in both of these sets? This problem is NP-hard because it admits a polynomial reduction from NAE 3-SAT. We construct a reduction that is polynomial both in the length of the instance and in k, which answers a recent question of Karpiski.

The edges of a graph are assigned weights and passage times which are assumed to be positive integers. We present a parallel algorithm for finding the shortest path whose total weight is smaller than a pre-determined value. In each step the processing elements are not analyzing the entire graph. Instead they are focusing on a subset of vertices called active vertices. The set of active vertices at time t is related to the boundary of the ball \(B_t\) of radius t in the first passage percolation metric. Although it is believed that the number of active vertices is an order of magnitude smaller than the size of the graph, we prove that this need not be the case with an example of a graph for which the active vertices form a large fractal. We analyze an OpenCL implementation of the algorithm on GPU for cubes in \(\mathbb Z^d\).

In this paper, we introduce a graph multi-coloring problem where each vertex must be assigned a given number of different colors, represented as integers, and no two adjacent vertices can share a common color. In the variant considered, the number of available colors is such that not all vertices can be colored. Furthermore, there is a bound on the number of vertices which can be assigned the same color. A gain is associated with each vertex and the first objective is to maximize the total gain over all colored vertices. Secondary objectives consider the sequence of colors assigned to each vertex. More precisely, the range and the number of interruptions must be minimized, where the range corresponds to the difference between the largest and smallest colors assigned to a vertex. This variant of the graph multi-coloring problem is of interest because it can model practical job scheduling applications. An integer linear programming formulation is first proposed to address small-size instances. A construction heuristic, as well as local search methods, are then reported to tackle larger instances. The local search methods are based on several neighborhood structures, each one focusing on a specific property of the problem. Different ways to combine these neighborhood structures are also investigated.

In this study, we consider the problem of estimating the diameter of a graph, that is, the maximum distance between any two vertices, in linear time. We address a question posed in the literature—whether there exists an interesting graph class with arbitrarily large cycles for which breadth first search (BFS) would always return high-eccentricity vertices. We answer this question positively, defining a class of graphs that generalizes AT-free graphs and has no bound on the size of induced cycles, yet BFS always returns a vertex whose eccentricity is within a constant difference from the diameter. In addition, we consider the question—also explicitly stated in the literature—whether some variant of the so-called multisweep algorithm would always return a high-eccentricity vertex. We show that the answer is negative by describing a family of graphs for which no variant of multisweep BFS can return a vertex of eccentricity higher than half of the diameter plus a constant.

A set of vertices W is a resolving set of a graph G if every two vertices of G have distinct representations of distances with respect to the set W. The number of vertices in a smallest resolving set is called the metric dimension. This invariant has extensive applications in robotics, since the metric dimension can represent the minimum number of landmarks, which uniquely determine the position of a robot moving in a graph space. Finding the metric dimension of a graph is a non-deterministic polynomial-time hard problem. We present exact values of the metric dimension of several networks, which can be obtained as categorial products of graphs.

The complexity of the subgraph isomorphism problem where the pattern graph is of fixed size is well known to depend on the topology of the pattern graph. Here, we present two results which, in contrast, provide evidence that no topology of an induced subgraph of fixed size can be substantially easier to detect or count than an independent set of related size.We show that any fixed pattern graph having a maximum independent set of size k that is disjoint from other maximum independent sets is not easier to detect as an induced subgraph than an independent set of size k. It follows in particular that an induced path on 2 k - 1 vertices is not easier to detect than an independent set on k vertices, and that an induced cycle on 2k vertices is not easier to detect than an independent set on k vertices. In view of linear time upper bounds on the detection of induced path of length two and three, our lower bound is tight. Similar corollaries hold for the detection of induced complete bipartite graphs and an induced paw and its generalizations.We show also that for an arbitrary pattern graph H on k vertices with no isolated vertices, there is a simple subdivision of H, resulting from splitting each edge into a path of length four and attaching a distinct path of length three at each vertex of degree one, that is not easier to detect or count than an independent set on k vertices, respectively.Next, we show that the so-called diamond and its generalizations on k vertices are not easier to detect as induced subgraphs than an independent set on three vertices or an independent set on k vertices, respectively. For C 4 , we give a weaker evidence of its hardness in terms of an independent set on three vertices.Finally, we derive several results relating the complexity of the edge-colored variant of induced subgraph isomorphism to that of the standard variant.

Broadcasting is the process of dissemination of a message from one vertex (called originator) to all other vertices in the graph. This task is accomplished by placing a sequence of calls between neighboring vertices, where one call requires one unit of time and each call involves exactly two vertices. Each vertex can participate in one call per one unit of time. Determination of the broadcast time of a vertex x in arbitrary graph G is NP-complete. Problem can be solved in polynomial time for trees and some subclasses of cactus graphs. In this paper broadcasting in cactus graphs is studied. An algorithm that determines broadcast time of any originator with time complexity O(n) in k-restricted cactus graph (where k is constant) is given. Furthermore, another algorithm which calculates broadcast time for all vertices in k-restricted cactus graph within the same time complexity is outlined. The algorithm also provides an optimal broadcast scheme for every vertex. As a byproduct, broadcast center of a k-restricted cactus graph is computed.

An interconnection network is usually modeled as a graph, in which vertices and edges correspond to processor and communication links, respectively. Connectivity is an important measurement for the fault tolerant in interconnection network. Two vertices is maximally local-connected if the maximum number of internally vertex-disjoint paths between them equals the minimum degree of these two vertices. In this paper, we show that an n -dimensional Bubble-sort star graph is ( 2 n - 5 ) -fault-tolerant maximally local-connected and is also ( 2 n - 6 ) -fault-tolerant one-to-many maximally local-connected.

This paper introduces four graph orientation problems named MaximizeW-Light, MinimizeW-Light, MaximizeW-Heavy, and MinimizeW-Heavy, where W can be any fixed non-negative integer. In each of these problems, the input is an undirected graph G and the objective is to assign a direction to each edge in G so that the number of vertices with outdegree at most W or at least W in the resulting directed graph is maximized or minimized. We derive a number of results on the computational complexity and polynomial-time approximability of these problems for different values of W and various special classes of graphs. In particular, we show that Maximize 0-Light and Minimize 1-Heavy are equivalent to Maximum Independent Set and Minimum Vertex Cover, respectively, so by allowing the value of W to vary, we obtain a new, natural generalization of the two latter problems.

A set $D$ of vertices of a graph $G$ is locating if every two distinct vertices outside $D$ have distinct neighbors in $D$; that is, for distinct vertices $u$ and $v$ outside $D$, $N(u) \cap D \neq N(v) \cap D$, where $N(u)$ denotes the open neighborhood of $u$. If $D$ is also a dominating set (total dominating set), it is called a locating-dominating set (respectively, locating-total dominating set) of $G$. A graph $G$ is twin-free if every two distinct vertices of $G$ have distinct open and closed neighborhoods. It is conjectured [D. Garijo, A. Gonzalez and A. Marquez, The difference between the metric dimension and the determining number of a graph. Applied Mathematics and Computation 249 (2014), 487--501] and [F. Foucaud and M. A. Henning. Locating-total dominating sets in twin-free graphs: a conjecture. The Electronic Journal of Combinatorics 23 (2016), P3.9] respectively, that any twin-free graph $G$ without isolated vertices has a locating-dominating set of size at most one-half its order and a locating-total dominating set of size at most two-thirds its order. In this paper, we prove these two conjectures for the class of line graphs. Both bounds are tight for this class, in the sense that there are infinitely many connected line graphs for which equality holds in the bounds., Comment: 23 pages, 2 figures

A cut-vertex in a graph G is a vertex whose removal increases the number of connected components of G. An end-block of G is a block with a single cut-vertex. In this paper we establish upper bounds on the numbers of end-blocks and cut-vertices in a 4-regular graph G and claw-free 4-regular graphs. We characterize the extremal graphs achieving these bounds.

Kinematic chain isomorphism identification is a crucial issue in mechanism topology and an important application of Graph Isomorphism to mechanisms. In this paper, a kinematic chain is uniquely represented by a graph, and a fast deterministic algorithm called the Dividing and Matching Algorithm (DMA) is proposed. First, the vertices of each graph are divided by the degree. Then, vertex connection properties in a sub-graph and between sub-graphs are explored. Accordingly the expanded square degree and the correlation degree are proposed, based on which, the Dividing Vertex Algorithm (DVA) is developed to divide vertices into sets. Moreover, it is proved that only the vertices from the corresponding sets between two graphs are possible to be bijective or matched, which avoids exhaustive search. Eventually, a backtracking procedure is employed to match the vertices between corresponding sets by calling up DVA repeatedly. DMA detects whether the adjacency matrices of two graphs can be adjusted to be equivalent by changing the orders of vertices. Justifications for the reliability of each part of DMA are provided. The experiments and comparisons with existing algorithms show the effectiveness and efficiency of DMA.

We study zero-one laws for random distance graph with vertices in {?1, 0, 1} n depending on a set of parameters. We give some conditions under which sequences of random distance graphs obey or do not obey the zero-one law.

A set of vertices in a graph is perfect dominating if every vertex outside the set is adjacent to exactly one vertex in the set, and is neighborhood connected if the subgraph induced by its open neighborhood is connected. In any graph the full set of vertices is perfect dominating, and in every connected graph the full set of vertices is neighborhood connected. It is shown that(i) in a connected graph, if the only neighborhood connected perfect dominating set is the full set of vertices, then the full set of vertices is also the only perfect dominating set; and (ii) if $ r \ge 3 $ and $ n_1, \ldots ,n_r \ge 2 $, then in $K_{n_1,\ldots,n_r}$ the only perfect dominating set is the full set of vertices. Also, (iii) estimates are derived of how many edges can be removed from or added to $K_{n_1,\ldots ,n_r}$ while preserving the property described in (ii).

We define a community structure of a graph as a partition of the vertices into at least two sets with the property that each vertex has connections to relatively many vertices in its own set compared to any other set in the partition and refer to the sets in such a partition as communities. We show that it is NP-hard to compute a community containing a given set of vertices. On the other hand, we show how to compute a community structure in polynomial time for any connected graph containing at least four vertices except the star graph S n . Finally, we generalize our results and formally show that counterintuitive aspects are unavoidable for any definition of a community structure with a polynomial time algorithm for computing communities containing specific vertices.

The bandwidth of a graph G on n vertices is the minimum b such that the vertices of G can be labeled from 1 to n such that the labels of every pair of adjacent vertices differ by at most b. In this paper, we present a 2-approximation algorithm for the Bandwidth problem that takes worst-case O(1.9797^n)=O(3^0^.^6^2^1^7^n) time and uses polynomial space. This improves both the previous best 2- and 3-approximation algorithms of Cygan et al. which have O^*(3^n) and O^*(2^n) worst-case running time bounds, respectively. Our algorithm is based on constructing bucket decompositions of the input graph. A bucket decomposition partitions the vertex set of a graph into ordered sets (called buckets) of (almost) equal sizes such that all edges are either incident to vertices in the same bucket or to vertices in two consecutive buckets. The idea is to find the smallest bucket size for which there exists a bucket decomposition. The algorithm uses a divide-and-conquer strategy along with dynamic programming to achieve the improved time bound.

An acyclic k-coloring of a graph G is a mapping @f from the set of vertices of G to a set of k distinct colors such that no two adjacent vertices receive the same color and @f does not contain any bichromatic cycle. In this paper we prove that every planar graph with n vertices has a 1-subdivision that is acyclically 3-colorable (respectively, 4-colorable), where the number of division vertices is at most 2n-5 (respectively, n-3). On the other hand, we prove a 1.28n (respectively, 0.3n) lower bound on the number of division vertices for acyclic 3-colorings (respectively, 4-colorings) of planar graphs. Furthermore, we establish the NP-completeness of deciding acyclic 4-colorability for graphs with maximum degree 5 and for planar graphs with maximum degree 7.

For two graphs G and H their wreath product has vertex set in which two vertices and are adjacent whenever or and . Clearly, , where is an independent set on n vertices, is isomorphic to the complete m-partite graph in which each partite set has exactly n vertices. A 2-regular subgraph of the complete multipartite graph containing vertices of all but one partite set is called partial 2-factor. For an integer λ, denotes a graph G with uniform edge multiplicity λ. Let J be a set of integers. If can be partitioned into edge-disjoint partial 2-factors consisting cycles of lengths from J, then we say that has a -cycle frame. In this paper, we show that for and , there exists a -cycle frame of if and only if and . In fact our results completely solve the existence of a -cycle frame of .

The eccentricity of a vertex is the maximum distance from it to another vertex, and the average eccentricity of a graph is the mean eccentricity of a vertex. In this paper we introduce average edge and average vertex-edge mean eccentricities of a graph. Moreover, relations among these eccentricities for trees are provided as well as formulas for line graphs and cartesian product of graphs.

A labeling scheme is a method of distributing the information about the structure of a graph among its vertices by assigning short labels, such that a selected function on pairs of vertices can be computed using only their labels. A labeling scheme consists of an encoder that has access to the entire graph and assigns labels to vertices, and a decoder that has access to only the labels of a smaller set of vertices (typically a pair) and returns information about this subset (e.g., whether two vertices are adjacent, or the distance between them in the graph). The main objective is to minimize the maximum label size: the maximum number of bits used in a label of any vertex. Among the applications of labeling schemes are XML search engines, mapping services, and internet routing.

We develop several parallel algorithms for shortest distance queries in planar graphs that use graph partitioning in the preprocessing phase to precompute and store distances between selected pairs of vertices. In the query phase, given a pair of arbitrary vertices v and w, the stored information is used to find the distance between v and w fast. The algorithms are implemented and tested on a high performance cluster with upto 256 16-core CPUs and their performances are analyzed and compared.

A dominating set of a graph $G$ is a set $D$ of vertices of $G$ such that every vertex outside $D$ is adjacent to a vertex in $D$. A locating-dominating set of $G$ is a dominating set $D$ of $G$ with the additional property that every two distinct vertices outside $D$ have distinct neighbors in $D$; that is, for distinct vertices $u$ and $v$ outside $D$, $N(u) \cap D \neq N(v) \cap D$ where $N(u)$ denotes the open neighborhood of $u$. A graph is twin-free if every two distinct vertices have distinct open and closed neighborhoods. The location-domination number of $G$, denoted $\gamma_L(G)$, is the minimum cardinality of a locating-dominating set in $G$. Garijo, Gonzalez and Marquez [Applied Math. Computation 249 (2014), 487--501] posed the conjecture that for $n$ sufficiently large, the maximum value of the location-domination number of a twin-free, connected graph on $n$ vertices is equal to $\lfloor \frac{n}{2} \rfloor$. We propose the related (stronger) conjecture that if $G$ is a twin-free graph of order $n$ without isolated vertices, then $\gamma_L(G)\leq \frac{n}{2}$. We prove the conjecture for cubic graphs. We rely heavily on proof techniques from matching theory to prove our result., Comment: 16 pages; 4 figures

For a set S of vertices and the vertex v in a connected graph G, $$\displaystyle \max _{x \in S}dx,v$$ is called the S-eccentricity of v in G. The set of vertices with minimum S-eccentricity is called the S-center of G. Any set Aof vertices of G such that A is an S-center for some set S of vertices of G is called a center set. We identify the center sets of certain classes of graphs namely, Block graphs, $$K_{m,n}$$, $$K_n-e$$, wheel graphs, odd cycles and symmetric even graphs. A graph G is called center critical if there does not a exist proper subset S of the vertex set whose S-center is the center of the graph. Here we characterize this class of graphs.

We study the problem of deleting a minimum cost set of vertices from a given vertex-weighted graph in such a way that the resulting graph has no induced path on three vertices. This problem is often called cluster vertex deletion in the literature and admits a straightforward 3-approximation algorithm since it is a special case of the vertex cover problem on a 3-uniform hypergraph. Very recently, You et al.i¾ź[14] described an efficient 5/2-approximation algorithm for the unweighted version of the problem. Our main result is a 7/3-approximation algorithm for arbitrary weights, using the local ratio technique. We further conjecture that the problem admits a 2-approximation algorithm and give some support for the conjecture. This is in sharp constrast with the fact that the similar problem of deleting vertices to eliminate all triangles in a graph is known to be UGC-hard to approximate to within a ratio better than 3, as proved by Guruswami and Leei¾ź[7].

We suggest a new type of problem about distances in graphs and make several conjectures. As a first step towards proving them, we show that for sufficiently large values of n and k, a graph on n vertices that has no three vertices pairwise at distance k has at most (n ? k + 1)2/4 pairs of vertices at distance k.

We investigate the family of graphs with many large eigenvalues. It is not hard to see that every graph with many vertices of large degree that are pairwise at distance at least four from each other, has many large eigenvalues. We show that this does not hold if the vertices of large degree are at mutual distance three from each other. We explore this class of graphs further and provide some bounds on their eigenvalues.

Let [Formula: see text] be the set of unicyclic graphs with n vertices and k cut vertices. In this paper, we determine the unique graph with the maximal spectral radius among all graphs in [Formula: see text] for 1 ≤ k ≤ n - 3.

A set of vertices S in a graph is convex if it contains all vertices which belong to shortest paths between vertices in S. The convexity number c(G) of a graph G is the maximum cardinality of a convex set of vertices which does not contain all vertices of G. We prove NP-completeness of the problem to decide for a given bipartite graph G and an integer k whether c(G) ≥ k. Furthermore, we identify natural necessary extension properties of graphs of small convexity number and study the interplay between these properties and upper bounds on the convexity number.

In this paper, we give some results on Laplacian spectral radius of graphs with cut vertices, and as their applications, we also determine the unique graph with the largest Laplacian spectral radius among all unicyclic graphs with n vertices and diameter d, 3⩽d⩽n−3.

In this paper, we show that among all the connected graphs with n vertices and k cut vertices, the maximal signless Laplacian spectral radius is attained uniquely at the graph Gn,k, where Gn,k is obtained from the complete graph Kn-k by attaching paths of almost equal lengths to all vertices of Kn-k. We also give a new proof of the analogous result for the spectral radius of the connected graphs with n vertices and k cut vertices (see [A. Berman, X.-D. Zhang, On the spectral radius of graphs with cut vertices, J. Combin. Theory Ser. B 83 (2001) 233–240]). Finally, we discuss the limit point of the maximal signless Laplacian spectral radius.

In this paper, we continue the study of paired-domination in graphs introduced by Haynes and Slater (Networks 32 (1998), 199–206). A paired-dominating set of a graph G with no isolated vertex is a dominating set S of vertices whose induced subgraph has a perfect matching. The set S is called a differentiating-paired dominating set if for every pair of distinct vertices u and v in V(G), N[u]∩S≠N[v]∩S, where N[u] denotes the set consisting of u and all vertices adjacent to u. In this paper, we provide a constructive characterization of trees that do not have a differentiating-paired dominating set.

The local connectivity of two vertices is defined as the maximum number of internally vertex-disjoint paths between them. In this paper, we define two vertices as maximally local-connected, if the maximum number of internally vertex-disjoint paths between them equals the minimum degree of these two vertices. Moreover, we show that an (n-1)-regular Cayley graph generated by transposition tree is maximally local-connected, even if there are at most (n-3) faulty vertices in it, and prove that it is also (n-1)-fault-tolerant one-to-many maximally local-connected.

Let G be a graph in which each vertex can be in one of two states: on or off. In the σ-game, when you “push” a vertex v you change the state of all of its neighbors, while in the σ+-game you change the state of v as well. Given a starting configuration of on vertices, the object of both games is to reduce it, by a sequence of pushes, to the smallest possible number of on vertices. We show that any starting configuration in a graph with no isolated vertices can, by a sequence of pushes, be reduced to at most half on, and we characterize those graphs for which you cannot do better. The proofs use techniques from coding theory. In the lit-only versions of these two games, you can only push vertices which are on. We obtain some results on the minimum number of on vertices one can obtain in grid graphs in the regular and lit-only versions of both games.

Let U ( n , k ) be the set of unicyclic graphs with n vertices and k pendant vertices. In this paper, we determine the unique graph with the minimal least eigenvalue among all graphs in U ( n , k ) . The work is related with that of Guo [S.G. Guo, The spectral radius of unicyclic and bicyclic graphs with n vertices and k pendant vertices, Linear Algebra Appl. 408 (2005) 78–85], which determined the unicyclic graph with the maximal spectral radius in U ( n , k ) . We can observe that the extremal graph on the least eigenvalue is different from that on the spectral radius.

A graph is walk-regular if the number of cycles of length rooted at a given vertex is a constant through all the vertices. For a walk-regular graph G with d+1 different eigenvalues and spectrally maximum diameter D = d, we study the geometry of its d-cliques, that is, the sets of vertices which are mutually at distance d. When these vertices are projected onto an eigenspace of its adjacency matrix, we show that they form a regular tetrahedron and we compute its parameters. Moreover, the results are generalized to the case of k-walk-regular graphs, a family which includes both walk-regular and distance-regular graphs, and their t-cliques or vertices at distance t from each other.

Motivated by DNA rearrangements and DNA homologous recombination modeled in [A. Angeleska, N. Jonoska, M. Saito, L.F. Landweber, RNA-guided DNA assembly, Journal of Theoretical Biology, 248(4) (2007), 706-720], we investigate smoothings on graphs that consist of only 4-valent and 1-valent rigid vertices, called assembly graphs. An assembly graph can be seen as a representation of the DNA during certain recombination processes in which 4-valent vertices correspond to the alignment of the recombination sites. A single gene is modeled by a polygonal path in an assembly graph. A polygonal path makes a ''right-angle'' turn at every vertex, defining smoothings at the 4-valent vertices and therefore modeling the recombination process. We investigate the minimal number of polygonal paths visiting all vertices of a given graph exactly once, and show that for every positive integer n there are graphs that require at least n such polygonal paths. We show that there is an embedding in three-dimensional space of each assembly graph such that smoothing of vertices according to a given set of polygonal paths results in an unlinked graph. As some recombination processes may happen simultaneously, we characterize the subsets of vertices whose simultaneous smoothings keep a given gene in tact and give a characterization of all sequences of sets of vertices defining successive simultaneous smoothings that can realize complete gene rearrangement.

We consider the problem of simplifying a planar triangle mesh using edge contractions, under the restriction that the resulting vertices must be a subset of the input set. That is, contraction of an edge must be made onto one of its adjacent vertices, which results in removing the other adjacent vertex. We show that if the perimeter of the mesh consists of at most five vertices, then we can always find a vertex not on the perimeter which can be removed in this way. If the perimeter consists of more than five vertices such a vertex may not exist. In order to maintain a higher number of removable vertices under the above restriction, we study edge flips which can be performed in a visually smooth way. A removal of a vertex which is preceded by one such smooth operation is called a 2-step removal. Moreover, we introduce the possibility that the user defines "important" vertices (or edges) which have to remain intact. Given m such important vertices, or edges, we show that a simplification hierarchy of size O(n) and depth O( log (n/m)) can be constructed by 2-step removals in O(n) time, such that the simplified graph contains the m important vertices and edges, and at most O(m) other vertices from the input graph. In some triangulations, many vertices may not even be 2-step removable. In order to provide the option to remove such vertices, we also define and examine k-step removals. This increases the lower bound on the number of removable vertices.

We consider the minimum number of cliques needed to partition the edge set of D(G), the distance multigraph of a simple graph G. Equivalently, we seek to minimize the number of elements needed to label the vertices of a simple graph G by sets so that the distance between two vertices equals the cardinality of the intersection of their labels. We use a fractional analogue of this parameter to find lower bounds for the distance multigraphs of various classes of graphs. Some of the bounds are shown to be exact.

A set S of vertices in a graph G is called a paired-dominating set if it dominates V and 〈S〉 contains at least one perfect matching. We characterize the set of vertices of a tree that are contained in all minimum paired-dominating sets of the tree.

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).