The complexity of determining the rainbow vertex-connection of a graph

A vertex-colored graph is rainbow vertex-connected if any two vertices are connected by a path whose internal vertices have distinct colors, which was introduced by Krivelevich and Yuster. The rainbow vertex-connection of a connected graph G, denoted by rvc(G), is the smallest number of colors that are needed in order to make G rainbow vertex-connected. In this paper, we study the complexity of determining the rainbow vertex-connection of a graph and prove that computing rvc(G) is NP-Hard. Moreover, we show that it is already NP-Complete to decide whether rvc(G)=2. We also prove that the following problem is NP-Complete: given a vertex-colored graph G, check whether the given coloring makes G rainbow vertex-connected.     

Fast message dissemination in random geometric networks

We analyze information dissemination in random geometric networks, which consist of n nodes placed uniformly at random in the square ${[0,\sqrt{n}]^{2}}$ . In the corresponding graph two nodes u and v are connected by a (directed) edge, i.e., u is an (incoming) neighbor of v, if and only if the distance between u and v is smaller than the transmission radius assigned to u. In order to study the performance of distributed communication algorithms in such networks, we adopt here the ad-hoc radio communication model with no collision detection mechanism available. In this model the topology of network connections is not known in advance. Also a node v is capable of receiving a message from its neighbor u if u is the only (incoming) neighbor transmitting in a given step. Otherwise a collision occurs prompting interference that is not distinguishable from the background noise in the network. First, we consider networks modeled by random geometric graphs in which all nodes have the same radius ${r > \delta \sqrt{\log n}}$ , where δ is a sufficiently large constant. In such networks, we provide a rigorous study of the classical communication problem of distributed gossiping (all-to-all communication). We examine various scenarios depending on initial local knowledge and capabilities of network nodes. We show that in many cases an asymptotically optimal distributed O(D)-time gossiping is feasible, where D stands for the diameter of the network. Later, we consider networks in which the transmission radii of the nodes vary according to a power law distribution, i.e., any node is assigned a transmission radius r > r _min according to probability density function ρ(r) ~ r ^?α . More precisely, ${\rho(r) = (\alpha-1)r_{\min}^{\alpha-1} r^{-\alpha}}$ , where ${\alpha \in (1, 3)}$ and ${r_{\min} > \delta \sqrt{\log n}}$ with δ being a large constant. In this case, we develop a simple broadcasting algorithm that runs in time O(log log n) (i.e., O(D)) always surely, and we show that this result is asymptotically optimal. Finally, we consider networks in which any node is assigned a transmission radius r > c according to the probability density function ρ(r) =  (α?1)c ^α-1 r ^?α , where α is a constant from the same range as before and c is a constant. In this model the graph is usually not strongly connected, however, there is one giant component with Ω(n) nodes, and there is a directed path from each node of this giant component to every other node in the graph. We assume that the message which has to be disseminated is placed initially in one of the nodes of the giant component, and every node is aware of its own position in ${[0,\sqrt{n}] \times [0,\sqrt{n}]}$ . Then, we show that there exists a randomized algorithm which delivers the broadcast message to all nodes in the network in time O(D . (log log n)²), almost always surely, where D stands for the diameter of the giant component of the graph. One can conclude from our studies that setting the transmission radii of the nodes according to a power law distribution brings clear advantages. In particular, one can design energy efficient radio networks with low average transmission radius, in which broadcasting can be performed exponentially faster than in the (extensively studied) case where all nodes have the uniform low transmission power.     

On the Expansion and Diameter of Bluetooth-Like Topologies

The routing capabilities of an interconnection network are strictly related to its bandwidth and latency characteristics, which are in turn quantifiable through the graph-theoretic concepts of expansion and diameter. This paper studies expansion and diameter of a family of subgraphs of the random geometric graph, which closely model the topology induced by the device discovery phase of Bluetooth-based ad hoc networks. The main feature modeled by any such graph, denoted as BT(r(n),c(n)), is the small number c(n) of links that each of the n devices (vertices) may establish with those located within its communication range r(n). First, tight bounds are proved on the expansion of BT(r(n),c(n)) for the whole set of functions r(n) and c(n) for which connectivity has been established in previous works. Then, by leveraging on the expansion result, nearly-tight upper and lower bounds on the diameter of BT(r(n),c(n)) are derived. In particular, we show asymptotically tight bounds on the diameter when the communication range is near the minimum needed for connectivity, the typical scenario considered in practical applications.     

Node bisectors of Cayley graphs

A node bisector of a graph Γ is a subset Ω of the nodes of Γ such that Γ may be expressed as the disjoint union $$\Gamma = \Omega _1 \dot \cup \Omega \dot \cup \Omega _2 ,$$ , where $\left| {\Omega _1 } \right| \geqslant \frac{1}{3}\left| \Gamma \right|,\Omega _2 \geqslant \frac{1}{3}\left| \Gamma \right|$ , and where any path from Ω₁ to Ω₂ must pass through Ω. Suppose Γ is the Cayley graph of an abelian groupG with respect to a generating set of cardinalityr, regarded as an undirected graph. Then we show that Γ has a node bisector of order at mostc¦G ^1-1/r wherec is a constant depending only onr. We show that the exponent in this result is the best possible.     

Diameter and Broadcast Time of Random Geometric Graphs in Arbitrary Dimensions

A random geometric graph (RGG) is defined by placing n points uniformly at random in [0,n ^1/d ] ^d , and joining two points by an edge whenever their Euclidean distance is at most some fixed r. We assume that r is larger than the critical value for the emergence of a connected component with Ω(n) nodes. We show that, with high probability (w.h.p.), for any two connected nodes with a Euclidean distance of $\omega (\frac{\log n}{r^{d-1}} )$ , their graph distance is only a constant factor larger than their Euclidean distance. This implies that the diameter of the largest connected component is Θ(n ^1/d /r) w.h.p. We also prove that the condition on the Euclidean distance above is essentially tight. We also analyze the following randomized broadcast algorithm on RGGs. At the beginning, only one node from the largest connected component of the RGG is informed. Then, in each round, each informed node chooses a neighbor independently and uniformly at random and informs it. We prove that w.h.p. this algorithm informs every node in the largest connected component of an RGG within Θ(n ^1/d /r+logn) rounds.     

Hamiltonian connectivity and globally 3∗-connectivity of dual-cube extensive networks

In 2000, Li et al. introduced dual-cube networks, denoted by DC_n for n?1, using the hypercube family Q_n and showed the vertex symmetry and some fault-tolerant hamiltonian properties of DC_n. In this article, we introduce a new family of interconnection networks called dual-cube extensive networks, denoted by DCEN(G). Given any arbitrary graph G, DCEN(G) is generated from G using the similar structure of DC_n. We show that if G is a nonbipartite and hamiltonian connected graph, then DCEN(G) is hamiltonian connected. In addition, if G has the property that for any two distinct vertices u,v of G, there exist three disjoint paths between u and v such that these three paths span the graph G, then DCEN(G) preserves the same property. Furthermore, we prove that the similar results hold when G is a bipartite graph.     

Parameterized approximation of dominating set problems

A problem open for many years is whether there is an FPT algorithm that given a graph G and parameter k, either: (1) determines that G has no k-Dominating Set, or (2) produces a dominating set of size at most g(k), where g(k) is some fixed function of k. Such an outcome is termed an FPT approximation algorithm. We describe some results that begin to provide some answers. We show that there is no such FPT algorithm for g(k) of the form k+c (where c is a fixed constant, termed an additive FPT approximation), unless FPT=W[2]. We answer the analogous problem completely for the related Independent Dominating Set (IDS) problem, showing that IDS does not admit an FPT approximation algorithm, for any g(k), unless FPT=W[2].     

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.     

Approximate minimum weight matching on points ink-dimensional space

We study the problem of finding a minimum weight complete matching in the complete graph on a set V ofn points ink-dimensional space. The points are the vertices of the graph and the weight of an edge between any two points is the distance between the points under someL _q,-metric. We give anO((2c _q )^1.5k ?^?1.5k (α(n, n))^0.5 n ^1.5(logn)^2.5) algorithm for finding an almost minimum weight complete matching in such a graph, wherec _q =6k ^1/q for theL _q -metric, α is the inverse Ackermann function, and ? ≤ 1. The weight of the complete matching obtained by our algorithm is guaranteed to be at most (1 + ?) times the weight of a minimum weight complete matching.     

Exponential-time approximation of weighted set cover

The Set Cover problem belongs to a group of hard problems which are neither approximable in polynomial time (at least with a constant factor) nor fixed parameter tractable, under widely believed complexity assumptions. In recent years, many researchers design exact exponential-time algorithms for problems of that kind. The goal is getting the time complexity still of order O(cn), but with the constant c as small as possible. In this work we extend this line of research and we investigate whether the constant c can be made even smaller when one allows constant factor approximation.In fact, we describe a kind of approximation schemes—trade-offs between approximation factor and the time complexity. We use general transformations from exponential-time exact algorithms to approximations that are faster but still exponential-time. For example, we show that for any reduction rate r, one can transform any O^∗(cn)-time¹ algorithm for Set Cover into a (1+lnr)-approximation algorithm running in time O^∗(cn/r). We believe that results of that kind extend the applicability of exact algorithms for NP-hard problems.     

An optimal parallel algorithm for c-vertex-ranking of trees

For a positive integer c, a c-vertex-ranking of a graph G=(V,E) is a labeling of the vertices of G with integers such that, for any label i, deletion of all vertices with labels >i leaves connected components, each having at most c vertices with label i. The c-vertex-ranking problem is to find a c-vertex-ranking of a given graph using the minimum number of ranks. In this paper we give an optimal parallel algorithm for solving the c-vertex-ranking problem on trees in O(log₂n) time using linear number of operations on the EREW PRAM model.     

The hub number of a graph

A hub set in a graph G is a set U⊆V(G) such that any two vertices outside U are connected by a path whose internal vertices lie in U. We prove that h(G)?hc(G)?γc(G)?h(G)+1, where h(G), hc(G), and γc(G), respectively, are the minimum sizes of a hub set in G, a hub set inducing a connected subgraph, and a connected dominating set. Furthermore, all graphs with γc(G)>hc(G)?4 are obtained by substituting graphs into three consecutive vertices of a cycle; this yields a polynomial-time algorithm to check whether hc(G)=γc(G).     

Traversing the machining graph of a pocket

A simple and linear-time algorithm is presented for solving the problem of traversing a machining graph with minimum retractions encountered in zigzag pocket machining and other applications. This algorithm finds a traversal of the machining graph of a general pocket P with N_h holes, such that the number of retractions in the traversal is no greater than OPT+N_h+N_r, where OPT is the (unknown) minimum number of retractions required by any algorithm and N_r is the number of reducible blocks in P (to be defined in the paper). When the step-over distance is small enough relative to the size of P, N_r becomes zero, and our result deviates from OPT by at most the number of holes in P, a significant improvement over the upper bound 5OPT+6N_h achieved [Proceedings of the Seventh ACM-SIAM Symposium on Discrete Algorithms, 1996; Algorithmica 2000 (26) 19]. In particular, if N_h is zero as well, i.e. when P has no holes, the proposed algorithm outputs an optimal solution. A novel computational modeling tool called block transition graph is introduced to formulate the traversal problem in a compact and concise form. Efficient algorithms are then presented for traversing this graph, which in turn gives rise to the major result.     

Collective Tree Spanners in Graphs with Bounded Parameters

In this paper we study collective additive tree spanners for special families of graphs including planar graphs, graphs with bounded genus, graphs with bounded tree-width, graphs with bounded clique-width, and graphs with bounded chordality. We say that a graph G=(V,E) admits a system of μ collective additive tree r -spanners if there is a system $\mathcal{T}(G)In this paper we study collective additive tree spanners for special families of graphs including planar graphs, graphs with bounded genus, graphs with bounded tree-width, graphs with bounded clique-width, and graphs with bounded chordality. We say that a graph G=(V,E) admits a system of μ collective additive tree r -spanners if there is a system T(G)\mathcal{T}(G) of at most μ spanning trees of G such that for any two vertices x,y of G a spanning tree T ? T(G)T\in\mathcal{T}(G) exists such that d _T (x,y)≤d _G (x,y)+r. We describe a general method for constructing a “small” system of collective additive tree r-spanners with small values of r for “well” decomposable graphs, and as a byproduct show (among other results) that any weighted planar graph admits a system of O(?n)O(\sqrt{n}) collective additive tree 0-spanners, any weighted graph with tree-width at most k−1 admits a system of klog ₂ n collective additive tree 0-spanners, any weighted graph with clique-width at most k admits a system of klog _3/2 n collective additive tree (2w)(2\mathsf{w}) -spanners, and any weighted graph with size of largest induced cycle at most c admits a system of log ₂ n collective additive tree (2?c/2?w)(2\lfloor c/2\rfloor\mathsf{w}) -spanners and a system of 4log ₂ n collective additive tree (2(?c/3?+1)w)(2(\lfloor c/3\rfloor +1)\mathsf {w}) -spanners (here, w\mathsf{w} is the maximum edge weight in G). The latter result is refined for weighted weakly chordal graphs: any such graph admits a system of 4log ₂ n collective additive tree (2w)(2\mathsf{w}) -spanners. Furthermore, based on this collection of trees, we derive a compact and efficient routing scheme for those families of graphs.     

On identifying codes that are robust against edge changes

Assume that G = (V, E) is an undirected graph, and C ⊆ V. For every v ∈ V, denote I_r(G; v) = {u ∈ C: d(u,v) ≤ r}, where d(u,v) denotes the number of edges on any shortest path from u to v in G. If all the sets I_r(G; v) for v ∈ V are pairwise different, and none of them is the empty set, the code C is called r-identifying. The motivation for identifying codes comes, for instance, from finding faulty processors in multiprocessor systems or from location detection in emergency sensor networks. The underlying architecture is modelled by a graph. We study various types of identifying codes that are robust against six natural changes in the graph; known or unknown edge deletions, additions or both. Our focus is on the radius r = 1. We show that in the infinite square grid the optimal density of a 1-identifying code that is robust against one unknown edge deletion is 1/2 and the optimal density of a 1-identifying code that is robust against one unknown edge addition equals 3/4 in the infinite hexagonal mesh. Moreover, although it is shown that all six problems are in general different, we prove that in the binary hypercube there are cases where five of the six problems coincide.     

Uniqueness Results for Image Reconstruction from Features on Curves in α-Scale Spaces

A sufficient condition is presented for two-dimensional images on a finite rectangular domain Ω=(?A,A)×(?B,B) to be completely determined by features on curves t?(ξ(t),t) in the three-dimensional domain Ω×(0,∞) of an α-scale space. For any fixed finite set of points in the image, the values of the α-scale space at these points at all scales together do not provide sufficient information to reconstruct the image, even if spatial derivatives up to any order are included as well. On the other hand, the image is completely fixed by the values of the scale space and its derivative along any straight line in Ω×(0,∞) for which ξ:(0,∞)→Ω is linear but not constant. A similar result holds for curves for which ξ is of the form ξ(t)=(ξ ₁(t),0) with ξ ₁ periodic and not constant. If the locations at which the scale space is evaluated form a curve on a cylinder in Ω×(0,∞) with some periodic structure, like a helix, then it is sufficient to evaluate the α-scale space without spatial derivatives.     

On vertex ranking of a starlike graph

A vertex coloring c:V→{1,2,…,t} of a graph G=(V,E) is a vertex t-ranking if for any two vertices of the same color every path between them contains a vertex of larger color. The vertex ranking number χ_r(G) is the smallest value of t such that G has a vertex t-ranking. A χ_r(G)-ranking of G is said to be an optimal vertex ranking. In this paper, we present an O(|V|+|E|) time algorithm for finding an optimal vertex ranking of a starlike graph G=(V,E). Our result implies that an optimal vertex ranking of a split graph can be computed in linear time.     

The super laceability of the hypercubes

A k-containerC(u,v) of a graph G is a set of k disjoint paths joining u to v. A k-container C(u,v) is a k∗-container if every vertex of G is incident with a path in C(u,v). A bipartite graph G is k∗-laceable if there exists a k∗-container between any two vertices u, v from different partite set of G. A bipartite graph G with connectivity k is super laceable if it is i∗-laceable for all i?k. A bipartite graph G with connectivity k is f-edge fault-tolerant super laceable if G−F is i∗-laceable for any 1?i?k−f and for any edge subset F with |F|=f<k−1. In this paper, we prove that the hypercube graph Q_r is super laceable. Moreover, Q_r is f-edge fault-tolerant super laceable for any f?r−2.     

Computations on Nondeterministic Cellular Automata

This work concerns the trade-offs between the dimension and the time and space complexity of computations on nondeterministic cellular automata. We assume that the space complexity is the diameter of area in space involved in computation. It is proved that (1) every nondeterministic cellular automata (NCA) of dimensionr, computing a predicatePwith time complexityT(n) and space complexityS(n) can be simulated byr-dimensional NCA with time and space complexityO(T^1/(r+1)S^r/(r+1)) and byr+1 dimensional NCA with time and space complexityO(T^1/2+S), whereTandSare functions constructible in time, (2) for any predicatePand integerr>1 if is a fastestr-dimensional NCA computingPwith time complexityT(n) and space complexityS(n), thenT=O(S), and (3) ifT_{r, P}is the time complexity of a fastestr-dimensional NCA computing predicatePthenT_r+1,P=O((T_{r, P})^1−r/(r+1)2),T_r+1,P=O((T_{r, P})^1+2/r).Similar problems for deterministic cellular automata (CA) are discussed.     

Relaxed Spanners for Directed Disk Graphs

Let (V,δ) be a finite metric space, where V is a set of n points and δ is a distance function defined for these points. Assume that (V,δ) has a doubling dimension d and assume that each point p∈V has a disk of radius r(p) around it. The disk graph that corresponds to V and r(?) is a directed graph I(V,E,r), whose vertices are the points of V and whose edge set includes a directed edge from p to q if δ(p,q)≤r(p). In Peleg and Roditty (Proc. 7th Int. Conf. on Ad-Hoc Networks and Wireless (AdHoc-NOW), pp. 622–633, 2008) we presented an algorithm for constructing a (1+?)-spanner of size O(n? ^?d logM), where M is the maximal radius r(p). The current paper presents two results. The first shows that the spanner of Peleg and Roditty (in Proc. 7th Int. Conf. on Ad-Hoc Networks and Wireless (AdHoc-NOW), pp. 622–633, 2008) is essentially optimal, i.e., for metrics of constant doubling dimension it is not possible to guarantee a spanner whose size is independent of M. The second result shows that by slightly relaxing the requirements and allowing a small augmentation of the radius assignment, considerably better spanners can be constructed. In particular, we show that if it is allowed to use edges of the disk graph I(V,E,r _1+? ), where r _1+? (p)=(1+?)?r(p) for every p∈V, then it is possible to get a (1+?)-spanner of size O(n/? ^d ) for I(V,E,r). Our algorithm is simple and can be implemented efficiently.