English

Time-Space Trade-offs for Triangulations and Voronoi Diagrams

Computational Geometry 2020-10-05 v3 Data Structures and Algorithms

Abstract

Let SS be a planar nn-point set. A triangulation for SS is a maximal plane straight-line graph with vertex set SS. The Voronoi diagram for SS is the subdivision of the plane into cells such that all points in a cell have the same nearest neighbor in SS. Classically, both structures can be computed in O(nlogn)O(n \log n) time and O(n)O(n) space. We study the situation when the available workspace is limited: given a parameter s{1,,n}s \in \{1, \dots, n\}, an ss-workspace algorithm has read-only access to an input array with the points from SS in arbitrary order, and it may use only O(s)O(s) additional words of Θ(logn)\Theta(\log n) bits for reading and writing intermediate data. The output should then be written to a write-only structure. We describe a deterministic ss-workspace algorithm for computing an arbitrary triangulation of SS in time O(n2/s+nlognlogs)O(n^2/s + n \log n \log s ) and a randomized ss-workspace algorithm for finding the Voronoi diagram of SS in expected time O((n2/s)logs+nlogslogs)O((n^2/s) \log s + n \log s \log^*s).

Keywords

Cite

@article{arxiv.1507.03403,
  title  = {Time-Space Trade-offs for Triangulations and Voronoi Diagrams},
  author = {Matias Korman and Wolfgang Mulzer and Andre van Renssen and Marcel Roeloffzen and Paul Seiferth and Yannik Stein},
  journal= {arXiv preprint arXiv:1507.03403},
  year   = {2020}
}

Comments

17 pages, 4 figures, a preliminary version appeared in WADS 2015