Computing Dominating Sets in Disk Graphs with Centers in Convex Position
Anastasiia Tkachenko, Haitao Wang
TL;DR
This work proves that the dominating set problem on disk graphs with centers in convex position is solvable in polynomial time, extending beyond the unit-disk setting. The authors introduce a line-separable structural property and a Voronoi-based partitioning to decompose the problem into tractable subproblems, which are then solved via dynamic programming using rank-$t$ centers. The weighted variant runs in $O(k^2n^3\log^2 n)$ time (yielding $O(n^5\log^2 n)$ when $k=n$), while the unweighted case achieves $O(k^2n\log^2 n)$ time (and $O(n^5\log^2 n)$ in the full-scale bound). A key contribution is the construction of a scalable, structure-driven DP that leverages the line-separable property to manage subproblem interactions, enabling efficient computation of minimum-weight and minimum-cardinality dominating sets in disk graphs under convex-position constraints.
Abstract
Given a set $P$ of $n$ points in the plane and a collection of disks centered at these points, the disk graph $G(P)$ has vertex set $P$, with an edge between two vertices if their corresponding disks intersect. We study the dominating set problem in $G(P)$ under the special case where the points of $P$ are in convex position. The problem is NP-hard in general disk graphs. Under the convex position assumption, however, we present the first polynomial-time algorithm for the problem. Specifically, we design an $O(k^2 n \log^2 n)$-time algorithm, where $k$ denotes the size of a minimum dominating set. For the weighted version, in which each disk has an associated weight and the goal is to compute a dominating set of minimum total weight, we obtain an $O(n^5 \log^2 n)$-time algorithm.
