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Approximating the Minimum Spanning Tree Weight in Sublinear Time
 In Proceedings of the 28th Annual International Colloquium on Automata, Languages and Programming (ICALP
, 2001
"... We present a probabilistic algorithm that, given a connected graph G (represented by adjacency lists) of average degree d, with edge weights in the set {1,...,w}, and given a parameter 0 < ε < 1/2, estimates in time O(dwε−2 log dw ε) the weight of the minimum spanning tree of G with a relativ ..."
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Cited by 46 (6 self)
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We present a probabilistic algorithm that, given a connected graph G (represented by adjacency lists) of average degree d, with edge weights in the set {1,...,w}, and given a parameter 0 < ε < 1/2, estimates in time O(dwε−2 log dw ε) the weight of the minimum spanning tree of G with a relative error of at most ε. Note that the running time does not depend on the number of vertices in G. We also prove a nearly matching lower bound of Ω(dwε−2) on the probe and time complexity of any approximation algorithm for MST weight. The essential component of our algorithm is a procedure for estimating in time O(dε−2 log d ε) the number of connected components of an unweighted graph to within an additive error of εn. (This becomes O(ε−2 log 1 ε) for d = O(1).) The time bound is shown to be tight up to within the log d ε factor. Our connectedcomponents algorithm picks O(1/ε2) vertices in the graph and then grows “local spanning trees” whose sizes are specified by a stochastic process. From the local information collected in this way, the algorithm is able to infer, with high confidence, an estimate of the number of connected components. We then show how estimates on the number of components in various subgraphs of G can be used to estimate the weight of its MST. 1
Two Linear Time Algorithms for MST on Minor Closed Graph Classes
, 2002
"... This article presents two simple deterministic algorithms for finding the Minimum Spanning Tree in O(V + E) time for any proper class of graphs closed on graph minors, which includes planar graphs and graphs of bounded genus. Both algorithms require no a priori knowledge of the structure of th ..."
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Cited by 6 (0 self)
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This article presents two simple deterministic algorithms for finding the Minimum Spanning Tree in O(V + E) time for any proper class of graphs closed on graph minors, which includes planar graphs and graphs of bounded genus. Both algorithms require no a priori knowledge of the structure of the class except for its density; edge weights are only compared and no random access to data is needed.
The Diameter of the Minimum Spanning Tree of a Complete Graph
"... } be independent identically distributed weights for the edges of Kn. If Xi � = Xj for i � = j, then ..."
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Cited by 5 (1 self)
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} be independent identically distributed weights for the edges of Kn. If Xi � = Xj for i � = j, then
Documenta Math. 127 The Origins of Minimal Spanning Tree Algorithms –
"... of computing ..."
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