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Fine-Grained Complexity of Multiple Domination and Dominating Patterns in Sparse Graphs

Marvin Künnemann, Mirza Redzic

TL;DR

While the classic dominating set problem admits a rather limited improvement in sparse graphs, it is shown that natural variants studied in the literature admit much larger speed-ups, with a diverse set of possible running times.

Abstract

The study of domination in graphs has led to a variety of domination problems studied in the literature. Most of these follow the following general framework: Given a graph $G$ and an integer $k$, decide if there is a set $S$ of $k$ vertices such that (1) some inner property $φ(S)$ (e.g., connectedness) is satisfied, and (2) each vertex $v$ satisfies some domination property $ρ(S, v)$ (e.g., there is an $s\in S$ that is adjacent to $v$). Since many real-world graphs are sparse, we seek to determine the optimal running time of such problems in both the number $n$ of vertices and the number $m$ of edges in $G$. While the classic dominating set problem admits a rather limited improvement in sparse graphs (Fischer, Künnemann, Redzic SODA'24), we show that natural variants studied in the literature admit much larger speed-ups, with a diverse set of possible running times. Specifically, we obtain conditionally optimal algorithms for: 1) $r$-Multiple $k$-Dominating Set (each vertex must be adjacent to at least $r$ vertices in $S$): If $r\le k-2$, we obtain a running time of $(m/n)^{r} n^{k-r+o(1)}$ that is conditionally optimal assuming the 3-uniform hyperclique hypothesis. In sparse graphs, this fully interpolates between $n^{k-1\pm o(1)}$ and $n^{2\pm o(1)}$, depending on $r$. Curiously, when $r=k-1$, we obtain a randomized algorithm beating $(m/n)^{k-1} n^{1+o(1)}$ and we show that this algorithm is close to optimal under the $k$-clique hypothesis. 2) $H$-Dominating Set ($S$ must induce a pattern $H$). We conditionally settle the complexity of three such problems: (a) Dominating Clique ($H$ is a $k$-clique), (b) Maximal Independent Set of size $k$ ($H$ is an independent set on $k$ vertices), (c) Dominating Induced Matching ($H$ is a perfect matching on $k$ vertices).

Fine-Grained Complexity of Multiple Domination and Dominating Patterns in Sparse Graphs

TL;DR

While the classic dominating set problem admits a rather limited improvement in sparse graphs, it is shown that natural variants studied in the literature admit much larger speed-ups, with a diverse set of possible running times.

Abstract

The study of domination in graphs has led to a variety of domination problems studied in the literature. Most of these follow the following general framework: Given a graph and an integer , decide if there is a set of vertices such that (1) some inner property (e.g., connectedness) is satisfied, and (2) each vertex satisfies some domination property (e.g., there is an that is adjacent to ). Since many real-world graphs are sparse, we seek to determine the optimal running time of such problems in both the number of vertices and the number of edges in . While the classic dominating set problem admits a rather limited improvement in sparse graphs (Fischer, Künnemann, Redzic SODA'24), we show that natural variants studied in the literature admit much larger speed-ups, with a diverse set of possible running times. Specifically, we obtain conditionally optimal algorithms for: 1) -Multiple -Dominating Set (each vertex must be adjacent to at least vertices in ): If , we obtain a running time of that is conditionally optimal assuming the 3-uniform hyperclique hypothesis. In sparse graphs, this fully interpolates between and , depending on . Curiously, when , we obtain a randomized algorithm beating and we show that this algorithm is close to optimal under the -clique hypothesis. 2) -Dominating Set ( must induce a pattern ). We conditionally settle the complexity of three such problems: (a) Dominating Clique ( is a -clique), (b) Maximal Independent Set of size ( is an independent set on vertices), (c) Dominating Induced Matching ( is a perfect matching on vertices).
Paper Structure (20 sections, 44 theorems, 23 equations)

This paper contains 20 sections, 44 theorems, 23 equations.

Key Result

theorem 1

Let $k\geq 3$ and $r\leq k-2$ be fixed constants. Given a graph $G$ with $n$ vertices and $m$ edges we can solve $r$-Multiple $k$-Dominating Set in time $(m/n)^r n^{k-r+o(1)}$, assuming $\omega = 2$.

Theorems & Definitions (70)

  • theorem 1
  • theorem 2
  • theorem 3
  • proposition 1
  • theorem 4
  • theorem 5
  • theorem 6
  • theorem 7
  • lemma 1
  • theorem 8
  • ...and 60 more