On the Line-Separable Unit-Disk Coverage and Related Problems

TL;DR

This paper presents faster algorithms for line-separable unit-disk coverage problems and related geometric covering problems, improving previous computational complexity bounds significantly.

Contribution

The authors develop new algorithms with improved time complexities for line-separable unit-disk coverage, line-constrained coverage, and half-plane coverage problems.

Findings

Achieved an $O((n+m)\log(n+m))$ time algorithm for line-separable unit-disk coverage.

Improved the line-constrained coverage algorithm to $O((n+m)\log (m+ n)+m \log m\log n)$ time.

Reduced the half-plane coverage problem to $O(n^3\log n)$ and $O(n\log n)$ time for special cases.

Abstract

Given a set $P$ of $n$ points and a set $S$ of $m$ disks in the plane, the disk coverage problem asks for a smallest subset of disks that together cover all points of $P$. The problem is NP-hard. In this paper, we consider a line-separable unit-disk version of the problem where all disks have the same radius and their centers are separated from the points of $P$ by a line $\ell$. We present an $O((n+m)\log(n+m))$ time algorithm for the problem. This improves the previously best result of $O(nm+ n\log n)$ time. Our techniques also solve the line-constrained version of the problem, where centers of all disks of $S$ are located on a line $\ell$ while points of $P$ can be anywhere in the plane. Our algorithm runs in $O((n+m)\log (m+ n)+m \log m\log n)$ time, which improves the previously best result of $O(nm\log(m+n))$ time. In addition, our results lead to an algorithm of $O(n^3\log n)$ time for a half-plane coverage problem (given $n$ half-planes and $n$ points, find a smallest subset of half-planes covering all points); this improves the previously best algorithm of $O(n^4\log n)$ time. Further, if all half-planes are lower ones, our algorithm runs in $O(n\log n)$ time while the previously best algorithm takes $O(n^2\log n)$ time.