Elimination Distance to Dominated Clusters

2025-04-30

AI Summary

This paper studies the Elimination Distance to Dominated Clusters problem: given an undirected graph (G) and integers (k,d), determine whether at most (k) layers of vertices can be recursively removed so that each remaining connected component admits a dominating set of size at most (d). We present the first unified fixed-parameter tractable (FPT) algorithm parameterized by the semi-ladder index (ell), significantly improving the parameter dependence from (k+d+c) (where (c) is the degeneracy) to (k+d+ell), with runtime (f(k,d)cdot n^{O(d)}). We fully characterize the parameterized complexity and kernelizability of the problem with respect to parameters (k), (d), (ell), degeneracy (c), and maximum degree (Delta), resolving an open question posed by Bentert et al. Our results establish a near-complete complexity classification for this problem.

Technology Category

• Constraint Satisfaction and Optimization: Distributed CSP/Optimization
• Search and Optimization: Distributed Search
• Knowledge Representation and Reasoning: Computational Complexity of Reasoning

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Semantics and Knowledge: Scalable techniques for the creation, curation, publication, maintenance, and consumption of large, Web-based, structured, reusable, knowledge graphs and ontologies
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems

Abstract

In the Dominated Cluster Deletion problem we are given an undirected graph $G$ and integers $k$ and $d$ and the question is to decide whether there exists a set of at most $k$ vertices whose removal results in a graph in which each connected component has a dominating set of size at most $d$. In the Elimination Distance to Dominated Clusters problem we are again given an undirected graph $G$ and integers $k$ and $d$ and the question is to decide whether we can recursively delete vertices up to depth $k$ such that each remaining connected component has a dominating set of size at most $d$. Bentert et al.~[Bentert et al., MFCS 2024] recently provided an almost complete classification of the parameterized complexity of Dominated Cluster Deletion with respect to the parameters $k$, $d$, $c$, and $Delta$, where $c$ and $Delta$ are the degeneracy, and the maximum degree of the input graph, respectively. In particular, they provided a non-uniform algorithm with running time $f(k,d)cdot n^{O(d)}$. They left as an open problem whether the problem is fixed-parameter tractable with respect to the parameter $k+d+c$. We provide a uniform algorithm running in time $f(k,d)cdot n^{O(d)}$ for both Dominated Cluster Deletion and Elimination Distance to Dominated Clusters. We furthermore show that both problems are FPT when parameterized by $k+d+ell$, where $ell$ is the semi-ladder index of the input graph, a parameter that is upper bounded and may be much smaller than the degeneracy $c$, positively answering the open question of Bentert et al. We almost complete the picture by providing an almost full classification for the parameterized complexity and kernelization complexity of Elimination Distance to Dominated Clusters. The one difficult base case that remains open is whether treedepth (the case $d=0$) is NP-hard on graphs of bounded maximum degree.

Problem

• Decide vertex removal for small dominating sets in graphs
• Parameterized complexity of Dominated Cluster Deletion
• FPT algorithm for k+d+l in graph problems

Innovation

• Uniform algorithm with time f(k,d)⋅n^O(d)
• FPT parameterized by k+d+ℓ (semi-ladder index)
• Almost complete parameterized complexity classification