Dynamic Planar Voronoi Diagrams for General Distance Functions and their Algorithmic Applications
Abstract
We describe a new data structure for dynamic nearest neighbor queries in the plane with respect to a general family of distance functions. These include -norms and additively weighted Euclidean distances. Our data structure supports general (convex, pairwise disjoint) sites that have constant description complexity (e.g., points, line segments, disks, etc.). Our structure uses storage, and requires polylogarithmic update and query time, improving an earlier data structure of Agarwal, Efrat and Sharir that required time for an update and time for a query [SICOMP, 1999]. Our data structure has numerous applications. In all of them, it gives faster algorithms, typically reducing an factor in the previous bounds to polylogarithmic. In addition, we give here two new applications: an efficient construction of a spanner in a disk intersection graph, and a data structure for efficient connectivity queries in a dynamic disk graph.
Cite
@article{arxiv.1604.03654,
title = {Dynamic Planar Voronoi Diagrams for General Distance Functions and their Algorithmic Applications},
author = {Haim Kaplan and Wolfgang Mulzer and Liam Roditty and Paul Seiferth and Micha Sharir},
journal= {arXiv preprint arXiv:1604.03654},
year = {2020}
}
Comments
61 pages, 11 figures; a preliminary version appeared in SODA 2017