'Society for Industrial & Applied Mathematics (SIAM)'
Doi
Abstract
In this paper we present a sublinear-time (1+ε)-approximation randomized algorithm to estimate the weight of the minimum spanning tree of an n-point metric space. The running time of the algorithm is O(n/εO(1)). Since the full description of an n-point metric space is of size Θ(n2), the complexity of our algorithm is sublinear with respect to the input size. Our algorithm is almost optimal as it is not possible to approximate in o(n) time the weight of the minimum spanning tree to within any factor. We also show that no deterministic algorithm can achieve a B-approximation in o(n2/B3) time. Furthermore, it has been previously shown that no o(n2) algorithm exists that returns a spanning tree whose weight is within a constant times the optimum