2,561 research outputs found

    On the fixed-parameter tractability of the maximum connectivity improvement problem

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    In the Maximum Connectivity Improvement (MCI) problem, we are given a directed graph G=(V,E)G=(V,E) and an integer BB and we are asked to find BB new edges to be added to GG in order to maximize the number of connected pairs of vertices in the resulting graph. The MCI problem has been studied from the approximation point of view. In this paper, we approach it from the parameterized complexity perspective in the case of directed acyclic graphs. We show several hardness and algorithmic results with respect to different natural parameters. Our main result is that the problem is W[2]W[2]-hard for parameter BB and it is FPT for parameters VB|V| - B and ν\nu, the matching number of GG. We further characterize the MCI problem with respect to other complementary parameters.Comment: 15 pages, 1 figur

    Approximating subset kk-connectivity problems

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    A subset TVT \subseteq V of terminals is kk-connected to a root ss in a directed/undirected graph JJ if JJ has kk internally-disjoint vsvs-paths for every vTv \in T; TT is kk-connected in JJ if TT is kk-connected to every sTs \in T. We consider the {\sf Subset kk-Connectivity Augmentation} problem: given a graph G=(V,E)G=(V,E) with edge/node-costs, node subset TVT \subseteq V, and a subgraph J=(V,EJ)J=(V,E_J) of GG such that TT is kk-connected in JJ, find a minimum-cost augmenting edge-set FEEJF \subseteq E \setminus E_J such that TT is (k+1)(k+1)-connected in JFJ \cup F. The problem admits trivial ratio O(T2)O(|T|^2). We consider the case T>k|T|>k and prove that for directed/undirected graphs and edge/node-costs, a ρ\rho-approximation for {\sf Rooted Subset kk-Connectivity Augmentation} implies the following ratios for {\sf Subset kk-Connectivity Augmentation}: (i) b(ρ+k)+(3TTk)2H(3TTk)b(\rho+k) + {(\frac{3|T|}{|T|-k})}^2 H(\frac{3|T|}{|T|-k}); (ii) ρO(TTklogk)\rho \cdot O(\frac{|T|}{|T|-k} \log k), where b=1 for undirected graphs and b=2 for directed graphs, and H(k)H(k) is the kkth harmonic number. The best known values of ρ\rho on undirected graphs are min{T,O(k)}\min\{|T|,O(k)\} for edge-costs and min{T,O(klogT)}\min\{|T|,O(k \log |T|)\} for node-costs; for directed graphs ρ=T\rho=|T| for both versions. Our results imply that unless k=To(T)k=|T|-o(|T|), {\sf Subset kk-Connectivity Augmentation} admits the same ratios as the best known ones for the rooted version. This improves the ratios in \cite{N-focs,L}

    Approximating Source Location and Star Survivable Network Problems

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    In Source Location (SL) problems the goal is to select a mini-mum cost source set SVS \subseteq V such that the connectivity (or flow) ψ(S,v)\psi(S,v) from SS to any node vv is at least the demand dvd_v of vv. In many SL problems ψ(S,v)=dv\psi(S,v)=d_v if vSv \in S, namely, the demand of nodes selected to SS is completely satisfied. In a node-connectivity variant suggested recently by Fukunaga, every node vv gets a "bonus" pvdvp_v \leq d_v if it is selected to SS. Fukunaga showed that for undirected graphs one can achieve ratio O(klnk)O(k \ln k) for his variant, where k=maxvVdvk=\max_{v \in V}d_v is the maximum demand. We improve this by achieving ratio \min\{p^*\lnk,k\}\cdot O(\ln (k/q^*)) for a more general version with node capacities, where p=maxvVpvp^*=\max_{v \in V} p_v is the maximum bonus and q=minvVqvq^*=\min_{v \in V} q_v is the minimum capacity. In particular, for the most natural case p=1p^*=1 considered by Fukunaga, we improve the ratio from O(klnk)O(k \ln k) to O(ln2k)O(\ln^2k). We also get ratio O(k)O(k) for the edge-connectivity version, for which no ratio that depends on kk only was known before. To derive these results, we consider a particular case of the Survivable Network (SN) problem when all edges of positive cost form a star. We give ratio O(min{lnn,ln2k})O(\min\{\ln n,\ln^2 k\}) for this variant, improving over the best ratio known for the general case O(k3lnn)O(k^3 \ln n) of Chuzhoy and Khanna

    Approximating Minimum-Cost k-Node Connected Subgraphs via Independence-Free Graphs

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    We present a 6-approximation algorithm for the minimum-cost kk-node connected spanning subgraph problem, assuming that the number of nodes is at least k3(k1)+kk^3(k-1)+k. We apply a combinatorial preprocessing, based on the Frank-Tardos algorithm for kk-outconnectivity, to transform any input into an instance such that the iterative rounding method gives a 2-approximation guarantee. This is the first constant-factor approximation algorithm even in the asymptotic setting of the problem, that is, the restriction to instances where the number of nodes is lower bounded by a function of kk.Comment: 20 pages, 1 figure, 28 reference
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