English

Space-Efficient Plane-Sweep Algorithms

Data Structures and Algorithms 2016-04-25 v2

Abstract

We introduce space-efficient plane-sweep algorithms for basic planar geometric problems. It is assumed that the input is in a read-only array of nn items and that the available workspace is Θ(s)\Theta(s) bits, where lgnsnlgn\lg n \leq s \leq n \cdot \lg n. Three techniques that can be used as general tools in different space-efficient algorithms are introduced and employed within our algorithms. In particular, we give an almost-optimal algorithm for finding the closest pair among a set of nn points that runs in O(n2/s+nlgs)O(n^2/s + n \cdot \lg s) time. We also give a simple algorithm to enumerate the intersections of nn line segments that runs in O((n2/s2/3)lgs+k)O((n^2/s^{2/3}) \cdot \lg s + k) time, where kk is the number of intersections. The counting version can be solved in O((n2/s2/3)lgs)O((n^2/s^{2/3}) \cdot \lg s)~time. When the segments are axis-parallel, we give an O((n2/s)lg4/3s+n4/3lg1/3n)O((n^2/s) \cdot \lg^{4/3} s + n^{4/3} \cdot \lg^{1/3} n)-time algorithm for counting the intersections, and an algorithm for enumerating the intersections that runs in O((n2/s)lgslglgs+nlgs+k)O((n^2/s) \cdot \lg s \cdot \lg \lg s + n \cdot \lg s + k) time, where kk is the number of intersections. We finally present an algorithm that runs in O((n2/s+nlgs)(n/s)lgn)O((n^2/s + n \cdot \lg s) \cdot \sqrt{(n/s) \cdot \lg n}) time to calculate Klee's measure of axis-parallel rectangles.

Keywords

Cite

@article{arxiv.1507.01767,
  title  = {Space-Efficient Plane-Sweep Algorithms},
  author = {Amr Elmasry and Frank Kammer},
  journal= {arXiv preprint arXiv:1507.01767},
  year   = {2016}
}
R2 v1 2026-06-22T10:07:12.223Z