This paper presents a distributed algorithm that runs on an n-node unit ball graph (UBG) G residing in a metric space of constant doubling dimension, and constructs, for any ε > 0, a (1 + ε)-spanner H of G with maximum degree bounded above by a constant. In addition, we show that H is “lightweight”, in the following sense. Let ∆ denote the aspect ratio of G, that is, the ratio of the length of ...

Metric embedding plays an important role in a vast range of application areas such as computer vision, computational biology, machine learning, networking, statistics, and mathematical psychology, to name a few. The main criteria for the quality of an embedding is its average distortion over all pairs. A celebrated theorem of Bourgain states that every finite metric space on n points embeds in ...

We study the problem of approximating MST(P ), the Euclidean minimum spanning tree of a set P of n points in [0, 1], by a spanning tree of some subset Q ⊂ P . We show that if the weight of MST(P ) is to be approximated, then in general Q must be large. If the shape of MST(P ) is to be approximated, then this is always possible with a small Q. More specifically, for any 0 < ε < 1 we prove: (i) T...

Non-metric dissimilarity measures may arise in practice e.g. when objects represented by sensory measurements or by structural descriptions are compared. It is an open issue whether such non-metric measures should be corrected in some way to be metric or even Euclidean. The reason for such corrections is the fact that pairwise metric distances are interpreted in metric spaces, while Euclidean d...