A simple and linear time randomized algorithm for computing sparse spanners in weighted graphs

Let G = (V,E) be an undirected weighted graph on |V | = n vertices and |E| = m edges. A t‐spanner of the graph G, for any t ≥ 1, is a subgraph (V,E_S), E_S ⊆ E, such that the distance between any pair of vertices in the subgraph is at most t times the distance between them in the graph G. Computing a t‐spanner of minimum size (number of edges) has been a widely studied and well‐motivated problem in computer science. In this paper we present the first linear time randomized algorithm that computes a t‐spanner of a given weighted graph. Moreover, the size of the t‐spanner computed essentially matches the worst case lower bound implied by a 43‐year old girth lower bound conjecture made independently by Erdős, Bollobás, and Bondy & Simonovits. Our algorithm uses a novel clustering approach that avoids any distance computation altogether. This feature is somewhat surprising since all the previously existing algorithms employ computation of some sort of local or global distance information, which involves growing either breadth first search trees up to θ(t)‐levels or full shortest path trees on a large fraction of vertices. The truly local approach of our algorithm also leads to equally simple and efficient algorithms for computing spanners in other important computational environments like distributed, parallel, and external memory. © 2006 Wiley Periodicals, Inc. Random Struct. Alg., 2007     

Distributed algorithms for weighted problems in sparse graphs

We study distributed algorithms for three graph-theoretic problems in weighted trees and weighted planar graphs. For trees, we present an efficient deterministic distributed algorithm which finds an almost exact approximation of a maximum-weight matching. In addition, in the case of trees, we show how to approximately solve the minimum-weight dominating set problem. For planar graphs, we present an almost exact approximation for the maximum-weight independent set problem.     

Tree spanners in planar graphs

A tree t-spanner of a graph G is a spanning subtree T of G in which the distance between every pair of vertices is at most t times their distance in G. Spanner problems have received some attention, mostly in the context of communication networks. It is known that for general unweighted graphs, the problem of deciding the existence of a tree t-spanner can be solved in polynomial time for t=2, while it is NP-hard for any t⩾4; the case t=3 is open, but has been conjectured to be hard. In this paper, we consider tree spanners in planar graphs. We show that even for planar unweighted graphs, it is NP-hard to determine the minimum t for which a tree t-spanner exists. On the other hand, we give a polynomial algorithm for any fixed t that decides for planar unweighted graphs with bounded face length whether there is a tree t-spanner. Furthermore, we prove that it can be decided in polynomial time whether a planar unweighted graph has a tree t-spanner for t=3.     

On weighted directed graphs

The study of a mixed graph and its Laplacian matrix have gained quite a bit of interest among the researchers. Mixed graphs are very important for the study of graph theory as they provide a setup where one can have directed and undirected edges in the graph. In this article we present a more general structure, namely the weighted directed graphs and supply appropriate generalizations of several existing results for mixed graphs related to singularity of the corresponding Laplacian matrix. We also prove many new combinatorial results relating the Laplacian matrix and the graph structure.     

Approximation algorithms for the weighted independent set problem in sparse graphs

The approximability of the unweighted independent set problem has been analyzed in terms of sparseness parameters such as the average degree and inductiveness. In the weighted case, no corresponding results are possible for average degree, since adding vertices of small weight can decrease the average degree arbitrarily without significantly changing the approximation ratio. In this paper, we introduce two weighted measures, namely weighted average degree and weighted inductiveness, and analyze algorithms for the weighted independent set problem in terms of these parameters.     

On the number of sparse connected graphs

We present a short way of estimating the number of connected graphs with k vertices k + l edges, when k→∞, l = l(k)→∞ but l = o(k).     

On the independence number of sparse graphs

Let G be a regular graph of degree d on n points which contains no K_r (r ≥ 4). Let α be the independence number of G. Then we show for large d that α ≥ c(r)n . © 1995 John Wiley & Sons, Inc.     

On the enumeration of certain weighted graphs

We enumerate weighted simple graphs with a natural upper bound condition on the sum of the weight of adjacent vertices. We also compute the generating function of the numbers of these graphs, and prove that it is a rational function. In particular, we show that the generating function for connected bipartite simple graphs is of the form p₁(x)/(1-x)^m+1. For nonbipartite simple graphs, we get a generating function of the form p₂(x)/(1-x)^m+1(1+x)^l. Here m is the number of vertices of the graph, p₁(x) is a symmetric polynomial of degree at most m, p₂(x) is a polynomial of degree at most m+l, and l is a nonnegative integer. In addition, we give computational results for various graphs.     

On the spanning trees of weighted graphs

Given a weighted graph, letW ₁,W ₂,W ₃,... denote the increasing sequence of all possible distinct spanning tree weights. Settling a conjecture due to Kano, we prove that every spanning tree of weightW ₁ is at mostk–1 edge swaps away from some spanning tree of weightW _k . Three other conjectures posed by Kano are proven for two special classes of graphs. Finally, we consider the algorithmic complexity of generating a spanning tree of weightW _k .This work was supported in part by a grant from the AT&T foundation and NSF grant DCR-8351757.Primarily supported by a 1967 Science and Engineering Scholarship from the Natural Sciences and Engineering Research Council of Canada.     

Girth of sparse graphs

For each fixed k ≥ 0, we give an upper bound for the girth of a graph of order n and size n + k. This bound is likely to be essentially best possible as n → ∞. © 2002 Wiley Periodicals, Inc. J Graph Theory 39: 194–200, 2002; DOI 10.1002/jgt.10023     

On distance -dominating and -independent sets in sparse graphs

Dvořák [European J. Combin. 34 (2013), pp. 833–840] gave a bound on the minimum size of a distance -dominating set in terms of the maximum size of a distance -independent set and generalized coloring numbers, thus obtaining a constant-factor approximation algorithm for the parameters in any class of graphs with bounded expansion. We improve and clarify this dependence using a linear programming (LP)-based argument inspired by the work of Bansal and Umboh [Inform. Process. Lett. 122 (2017), pp. 21–24].     

On heavy paths in 2-connected weighted graphs

A weighted graph is a graph in which every edge is assigned a non-negative real number. In a weighted graph, the weight of a path is the sum of the weights of its edges, and the weighed degree of a vertex is the sum of the weights of the edges incident with it. In this paper we give three weighted degree conditions for the existence of heavy or Hamilton paths with one or two given end-vertices in 2-connected weighted graphs.     

Globally sparse vertex-ramsey graphs

For graphs G and F we write F → (G)¹_r if every r-coloring of the vertices of F results in a monochromatic copy of G. The global density m(F) of F is the maximum ratio of the number of edges to the number of vertices taken over all subgraphs of F. Let We show that The lower bound is achieved by complete graphs, whereas, for all r ≥ 2 and ? > 0, m_cr(S_k, r) > r - ? for sufficiently large k, where S_k is the star with k arms. In particular, we prove that