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83
Biconnectivity Approximations and Graph Carvings
, 1994
"... A spanning tree in a graph is the smallest connected spanning subgraph. Given a graph, how does one find the smallest (i.e., least number of edges) 2connected spanning subgraph (connectivity refers to both edge and vertex connectivity, if not specified) ? Unfortunately, the problem is known to be ..."
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Cited by 84 (3 self)
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A spanning tree in a graph is the smallest connected spanning subgraph. Given a graph, how does one find the smallest (i.e., least number of edges) 2connected spanning subgraph (connectivity refers to both edge and vertex connectivity, if not specified) ? Unfortunately, the problem is known to be NP hard. We consider the problem of finding a better approximation to the smallest 2connected subgraph, by an efficient algorithm. For 2edge connectivity our algorithm guarantees a solution that is no more than 3 2 times the optimal. For 2vertex connectivity our algorithm guarantees a solution that is no more than 5 3 times the optimal. The previous best approximation factor is 2 for each of these problems. The new algorithms (and their analyses) depend upon a structure called a carving of a graph, which is of independent interest. We show that approximating the optimal solution to within an additive constant is NP hard as well. We also consider the case where the graph has edge weigh...
Approximating minimum cost connectivity problems
 58 in Approximation algorithms and Metaheuristics, Editor
, 2007
"... ..."
Approximation Algorithms for Finding Highly Connected Subgraphs
, 1996
"... Contents 1 Introduction 2 1.1 Outline of Chapter : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 3 2 EdgeConnectivity Problems 3 2.1 Weighted EdgeConnectivity : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 3 2.2 Unweighted EdgeConnectivity : : : : : ..."
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Cited by 60 (1 self)
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Contents 1 Introduction 2 1.1 Outline of Chapter : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 3 2 EdgeConnectivity Problems 3 2.1 Weighted EdgeConnectivity : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 3 2.2 Unweighted EdgeConnectivity : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 4 2.2.1 2 EdgeConnectivity : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 4 2.2.2 EdgeConnectivity : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 8 3 VertexConnectivity Problems 11 3.1 Weighted VertexConnectivity : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 11 3.2 Unweighted VertexConnectivity : : : : : : : : : : : : : : : : : : : : : : : : : : : : : 12 3.2.1 2 VertexConnectivity : : : : : : : : : : : : : : : : :
Minimal EdgeCoverings of Pairs of Sets
, 1995
"... A new minmax theorem concerning bisupermodular functions on pairs of sets is proved. As a special case, we derive an extension of (A. Lubiw's extension of) E. Györi's theorem on intervals, W. Mader's theorem on splitting off edges in directed graphs, J. Edmonds' theorem on matroid partitions, and ..."
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Cited by 59 (13 self)
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A new minmax theorem concerning bisupermodular functions on pairs of sets is proved. As a special case, we derive an extension of (A. Lubiw's extension of) E. Györi's theorem on intervals, W. Mader's theorem on splitting off edges in directed graphs, J. Edmonds' theorem on matroid partitions, and an earlier result of the first author on the minimum number of new directed edges whose addition makes a digraph kedgeconnected. As another consequence, we solve the corresponding nodeconnectivity augmentation problem in directed graphs.
Power Optimization in FaultTolerant Topology Control Algorithms for Wireless Multihop Networks
 in Proceedings of the 9th Annual International Conference on Mobile Computing and Networking. 2003
, 2003
"... In ad hoc wireless networks, it is crucial to minimize power consumption while maintaining key network properties. This work studies power assignments of wireless devices that minimize power while maintaining kfault tolerance. Specifically, we require all links established by this power setting be ..."
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Cited by 56 (7 self)
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In ad hoc wireless networks, it is crucial to minimize power consumption while maintaining key network properties. This work studies power assignments of wireless devices that minimize power while maintaining kfault tolerance. Specifically, we require all links established by this power setting be symmetric and form a kvertex connected subgraph of the network graph. This problem is known to be NPhard. We show current heuristic approaches can use arbitrarily more power than the optimal solution. Hence, we seek approximation algorithms for this problem. We present three approximation algorithms. The first algorithm gives an O(kα)approximation where α is the best approximation factor for the related problem in wired networks (the best α so far is O(log k).) With a more careful analysis, we show our second (slightly more complicated) algorithm is an O(k)approximation. Our third algorithm assumes that the edge lengths of the network graph form a metric. In this case, we present simple and practical distributed algorithms for the cases of 2 and 3connectivity with constant approximation factors. We generalize this algorithm to obtain an O(k 2c+2)approximation for general kconnectivity (2 ≤ c ≤ 4 is the power attenuation exponent). Finally, we show that these approximation algorithms compare favorably with existing heuristics. We note that all algorithms presented in this paper can be used to minimize power while maintaining kedge connectivity with guaranteed approximation factors.
Computing All Small Cuts in an Undirected Network
 SIAM Journal on Discrete Mathematics
, 1994
"... : Let (N ) denote the weight of a minimum cut in an edgeweighted undirected network N , and n and m denote the numbers of vertices and edges, respectively. It is known that O(n 2k ) is an upper bound on the number of cuts with weights less than k(N ), where k 1 is a given constant. This paper rs ..."
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Cited by 31 (2 self)
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: Let (N ) denote the weight of a minimum cut in an edgeweighted undirected network N , and n and m denote the numbers of vertices and edges, respectively. It is known that O(n 2k ) is an upper bound on the number of cuts with weights less than k(N ), where k 1 is a given constant. This paper rst shows that all cuts of weights less than k(N ) can be enumerated in O(m 2 n + n 2k m) time without using the maximum ow algorithm. The paper then proves for k < 4 3 that 0 n 2 is a tight upper bound on the number of cuts of weights less than k(N ), and that all those cuts can be enumerated in O(m 2 n+mn 2 log n) time. Keywords: minimum cuts, graphs, edgesplitting, polynomial algorithm Abbreviated title: Computing Small Cuts AMS subject classications: 05C35, 05C40 1 Introduction Let N stand for an undirected network with its edges being weighted by nonnegative real numbers. Counting the number of cuts with small weights, and deriving upper and lower bounds on their...
Independence Free Graphs and Vertex Connectivity Augmentation
, 2001
"... Given an undirected graph G and a positive integer k, the kvertexconnectivity augmentation problem is to nd a smallest set F of new edges for which G+F is kvertexconnected. Polynomial algorithms for this problem have been found only for k 4 and a major open question in graph connectivity is w ..."
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Cited by 19 (0 self)
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Given an undirected graph G and a positive integer k, the kvertexconnectivity augmentation problem is to nd a smallest set F of new edges for which G+F is kvertexconnected. Polynomial algorithms for this problem have been found only for k 4 and a major open question in graph connectivity is whether this problem is solvable in polynomial time in general. In this
Edgeconnectivity augmentation with partition constraints
 SIAM J. Discrete Mathematics
, 1999
"... When k is even the minmax formula for the partitionconstrained problem is a natural generalization of [3]. However this generalization fails when k is odd. We show that at most one more edge is needed when k is odd and we characterize the graphs that require such an extra edge. ..."
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Cited by 17 (9 self)
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When k is even the minmax formula for the partitionconstrained problem is a natural generalization of [3]. However this generalization fails when k is odd. We show that at most one more edge is needed when k is odd and we characterize the graphs that require such an extra edge.