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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.

Computing Dominating Sets in Disk Graphs with Centers in Convex Position

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- centers. The weighted variant runs in time (yielding when ), while the unweighted case achieves time (and 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 of points in the plane and a collection of disks centered at these points, the disk graph has vertex set , with an edge between two vertices if their corresponding disks intersect. We study the dominating set problem in under the special case where the points of 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 -time algorithm, where 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 -time algorithm.
Paper Structure (29 sections, 18 theorems, 2 equations, 7 figures)

This paper contains 29 sections, 18 theorems, 2 equations, 7 figures.

Key Result

Lemma 1

Suppose $S$ is an optimal dominating set of $G(P)$. Then there exists a partition $\mathcal{A}$ of $P$ and a line-separable assignment $\phi : \mathcal{A}\rightarrow S$ such that (1) for every point $p_i\in S$, $p_i \in \mathcal{A}_{p_i}$, i.e., the group $\mathcal{A}_{p_i}$ contains $p_i$ itself, a

Figures (7)

  • Figure 1: Illustrating an example in which $|\mathcal{A}_{p_i}|=\Omega(n)$.
  • Figure 2: Illustrating the relative positions of points of $P$ (only their indices are shown): the circle represent $\mathcal{H}(P)$.
  • Figure 3: Illustrating $L_x$, $L_y$, and $L$.
  • Figure 4: Illustrating the sublists of $\mathcal{A}$, represented by the black solid arcs (the dotted circle represents $\mathcal{H}(P)$).
  • Figure 5: Illustrating the proof of Lemma \ref{['lem:correct20']}. For points of $P$, only their indices are shown. The red (resp., blue) dashed arc represents $L_1'$ (resp., $L_2'$). The red (resp., blue, green) solid arc represents $L_1$ (resp., $L_2$, $L$). The black solid arcs on the dotted circle represents sublists of $\mathcal{A}$.
  • ...and 2 more figures

Theorems & Definitions (33)

  • Lemma 1
  • proof
  • Lemma 2
  • proof
  • Definition 1
  • Definition 2
  • proof
  • proof
  • Lemma 3
  • Lemma 4
  • ...and 23 more