18,590 research outputs found
Improved Approximation Algorithms for Steiner Connectivity Augmentation Problems
The Weighted Connectivity Augmentation Problem is the problem of augmenting
the edge-connectivity of a given graph by adding links of minimum total cost.
This work focuses on connectivity augmentation problems in the Steiner setting,
where we are not interested in the connectivity between all nodes of the graph,
but only the connectivity between a specified subset of terminals.
We consider two related settings. In the Steiner Augmentation of a Graph
problem (-SAG), we are given a -edge-connected subgraph of a graph
. The goal is to augment by including links and nodes from of
minimum cost so that the edge-connectivity between nodes of increases by 1.
In the Steiner Connectivity Augmentation Problem (-SCAP), we are given a
Steiner -edge-connected graph connecting terminals , and we seek to add
links of minimum cost to create a Steiner -edge-connected graph for .
Note that -SAG is a special case of -SCAP.
All of the above problems can be approximated to within a factor of 2 using
e.g. Jain's iterative rounding algorithm for Survivable Network Design. In this
work, we leverage the framework of Traub and Zenklusen to give a -approximation for the Steiner Ring Augmentation Problem (SRAP):
given a cycle embedded in a larger graph and
a subset of terminals , choose a subset of links of minimum cost so that has 3 pairwise edge-disjoint paths
between every pair of terminals.
We show this yields a polynomial time algorithm with approximation ratio for -SCAP. We obtain an improved approximation
guarantee of for SRAP in the case that , which
yields a -approximation for -SAG for any
Connectivity and spanning trees of graphs
This dissertation focuses on connectivity, edge connectivity and edge-disjoint spanning trees in graphs and hypergraphs from the following aspects.;1. Eigenvalue aspect. Let lambda2(G) and tau( G) denote the second largest eigenvalue and the maximum number of edge-disjoint spanning trees of a graph G, respectively. Motivated by a question of Seymour on the relationship between eigenvalues of a graph G and bounds of tau(G), Cioaba and Wong conjectured that for any integers d, k ≥ 2 and a d-regular graph G, if lambda 2(G)) \u3c d -- 2k-1d+1 , then tau(G) ≥ k. They proved the conjecture for k = 2, 3, and presented evidence for the cases when k ≥ 4. We propose a more general conjecture that for a graph G with minimum degree delta ≥ 2 k ≥ 4, if lambda2(G) \u3c delta -- 2k-1d+1 then tau(G) ≥ k. We prove the conjecture for k = 2, 3 and provide partial results for k ≥ 4. We also prove that for a graph G with minimum degree delta ≥ k ≥ 2, if lambda2( G) \u3c delta -- 2k-1d +1 , then the edge connectivity is at least k. As corollaries, we investigate the Laplacian and signless Laplacian eigenvalue conditions on tau(G) and edge connectivity.;2. Network reliability aspect. With graphs considered as natural models for many network design problems, edge connectivity kappa\u27(G) and maximum number of edge-disjoint spanning trees tau(G) of a graph G have been used as measures for reliability and strength in communication networks modeled as graph G. Let kappa\u27(G) = max{lcub}kappa\u27(H) : H is a subgraph of G{rcub}. We present: (i) For each integer k \u3e 0, a characterization for graphs G with the property that kappa\u27(G) ≤ k but for any additional edge e not in G, kappa\u27(G + e) ≥ k + 1. (ii) For any integer n \u3e 0, a characterization for graphs G with |V(G)| = n such that kappa\u27(G) = tau( G) with |E(G)| minimized.;3. Generalized connectivity. For an integer l ≥ 2, the l-connectivity kappal( G) of a graph G is defined to be the minimum number of vertices of G whose removal produces a disconnected graph with at least l components or a graph with fewer than l vertices. Let k ≥ 1, a graph G is called (k, l)-connected if kappa l(G) ≥ k. A graph G is called minimally (k, l)-connected if kappal(G) ≥ k but ∀e ∈ E( G), kappal(G -- e) ≤ k -- 1. A structural characterization for minimally (2, l)-connected graphs and some extremal results are obtained. These extend former results by Dirac and Plummer on minimally 2-connected graphs.;4. Degree sequence aspect. An integral sequence d = (d1, d2, ···, dn) is hypergraphic if there is a simple hypergraph H with degree sequence d, and such a hypergraph H is a realization of d. A sequence d is r-uniform hypergraphic if there is a simple r- uniform hypergraph with degree sequence d. It is proved that an r-uniform hypergraphic sequence d = (d1, d2, ···, dn) has a k-edge-connected realization if and only if both di ≥ k for i = 1, 2, ···, n and i=1ndi≥ rn-1r-1 , which generalizes the formal result of Edmonds for graphs and that of Boonyasombat for hypergraphs.;5. Partition connectivity augmentation and preservation. Let k be a positive integer. A hypergraph H is k-partition-connected if for every partition P of V(H), there are at least k(| P| -- 1) hyperedges intersecting at least two classes of P. We determine the minimum number of hyperedges in a hypergraph whose addition makes the resulting hypergraph k-partition-connected. We also characterize the hyperedges of a k-partition-connected hypergraph whose removal will preserve k-partition-connectedness
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Graph Connectivity: Approximation Algorithms and Applications to Protein-Protein Interaction Networks
A graph is connected if there is a path between any two of its vertices and k-connected if there are at least k disjoint paths between any two vertices. A graph is k-edge-connected if none of the k paths share any edges and k-vertex-connected (or k-connected) if they do not share any intermediate vertices. We examine some problems related to k-connectivity and an application.
We have looked at the k-edge-connected spanning subgraph problem: given a k-edge-connected graph, find the smallest subgraph that includes all vertices and is still k-edge-connected. We improved two algorithms for approximating solutions to this problem. The first algorithm transforms the problem into an integer linear program, relaxes it into a real-valued linear program and solves it, then obtains an approximate solution to the original problem by rounding non-integer values. We have improved the approximation ratio by giving a better scheme for rounding the edges and bounding the number of fractional edges. The second algorithm finds a subgraph where every vertex has a minimum degree, then augments the subgraph by adding edges until it is k-edgeconnected. We improve this algorithm by bounding the number of edges that could be added in the augmentation step.
We have also applied the idea of k-connectivity to protein-protein interaction (PPI) networks, biological graphs where vertices represent proteins and edges represent experimentally determined physical interactions. Because few PPI networks are even 1-connected, we have looked for highly connected subgraphs of these graphs. We developed algorithms to find the most highly connected subgraphs of a graph. We applied our algorithms to a large network of yeast protein interactions and found that the most highly connected subgraph was a 16-connected subgraph of membrane proteins that had never before been identified as a module and is of interest to biologists. We also looked at graphs of proteins known to be co-complexed and found that a significant number contained 3- connected subgraphs, one of the features that most differentiated complexes from random graphs
Minimum Input Selection for Structural Controllability
Given a linear system , where is an matrix
with nonzero entries, we consider the problem of finding the smallest set
of state variables to affect with an input so that the resulting system is
structurally controllable. We further assume we are given a set of "forbidden
state variables" which cannot be affected with an input and which we have
to avoid in our selection. Our main result is that this problem can be solved
deterministically in operations
Grad and classes with bounded expansion I. decompositions
We introduce classes of graphs with bounded expansion as a generalization of
both proper minor closed classes and degree bounded classes. Such classes are
based on a new invariant, the greatest reduced average density (grad) of G with
rank r, grad r(G). For these classes we prove the existence of several
partition results such as the existence of low tree-width and low tree-depth
colorings. This generalizes and simplifies several earlier results (obtained
for minor closed classes)
Approximating subset -connectivity problems
A subset of terminals is -connected to a root in a
directed/undirected graph if has internally-disjoint -paths for
every ; is -connected in if is -connected to every
. We consider the {\sf Subset -Connectivity Augmentation} problem:
given a graph with edge/node-costs, node subset , and
a subgraph of such that is -connected in , find a
minimum-cost augmenting edge-set such that is
-connected in . The problem admits trivial ratio .
We consider the case and prove that for directed/undirected graphs and
edge/node-costs, a -approximation for {\sf Rooted Subset -Connectivity
Augmentation} implies the following ratios for {\sf Subset -Connectivity
Augmentation}: (i) ; (ii) , where
b=1 for undirected graphs and b=2 for directed graphs, and is the th
harmonic number. The best known values of on undirected graphs are
for edge-costs and for
node-costs; for directed graphs for both versions. Our results imply
that unless , {\sf Subset -Connectivity Augmentation} admits
the same ratios as the best known ones for the rooted version. This improves
the ratios in \cite{N-focs,L}
Non-Uniform Robust Network Design in Planar Graphs
Robust optimization is concerned with constructing solutions that remain
feasible also when a limited number of resources is removed from the solution.
Most studies of robust combinatorial optimization to date made the assumption
that every resource is equally vulnerable, and that the set of scenarios is
implicitly given by a single budget constraint. This paper studies a robustness
model of a different kind. We focus on \textbf{bulk-robustness}, a model
recently introduced~\cite{bulk} for addressing the need to model non-uniform
failure patterns in systems.
We significantly extend the techniques used in~\cite{bulk} to design
approximation algorithm for bulk-robust network design problems in planar
graphs. Our techniques use an augmentation framework, combined with linear
programming (LP) rounding that depends on a planar embedding of the input
graph. A connection to cut covering problems and the dominating set problem in
circle graphs is established. Our methods use few of the specifics of
bulk-robust optimization, hence it is conceivable that they can be adapted to
solve other robust network design problems.Comment: 17 pages, 2 figure
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