A tight bound on approximating arbitrary metrics by tree metrics

J Fakcharoenphol, S Rao, K Talwar - … of the thirty-fifth annual ACM …, 2003 - dl.acm.org
Proceedings of the thirty-fifth annual ACM symposium on Theory of computing, 2003dl.acm.org
In this paper, we show that any n point metric space can be embedded into a distribution
over dominating tree metrics such that the expected stretch of any edge is O (log n). This
improves upon the result of Bartal who gave a bound of O (log n log log n). Moreover, our
result is existentially tight; there exist metric spaces where any tree embedding must have
distortion Ω (log n)-distortion. This problem lies at the heart of numerous approximation and
online algorithms including ones for group Steiner tree, metric labeling, buy-at-bulk network …
In this paper, we show that any n point metric space can be embedded into a distribution over dominating tree metrics such that the expected stretch of any edge is O(log n). This improves upon the result of Bartal who gave a bound of O(log n log log n). Moreover, our result is existentially tight; there exist metric spaces where any tree embedding must have distortion Ω(log n)-distortion. This problem lies at the heart of numerous approximation and online algorithms including ones for group Steiner tree, metric labeling, buy-at-bulk network design and metrical task system. Our result improves the performance guarantees for all of these problems.
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