Width Parameterizations for Knot-free Vertex Deletion on Digraphs (1910.01783v1)
Abstract: A knot in a directed graph $G$ is a strongly connected subgraph $Q$ of $G$ with at least two vertices, such that no vertex in $V(Q)$ is an in-neighbor of a vertex in $V(G)\setminus V(Q)$. Knots are important graph structures, because they characterize the existence of deadlocks in a classical distributed computation model, the so-called OR-model. Deadlock detection is correlated with the recognition of knot-free graphs as well as deadlock resolution is closely related to the {\sc Knot-Free Vertex Deletion (KFVD)} problem, which consists of determining whether an input graph $G$ has a subset $S \subseteq V(G)$ of size at most $k$ such that $G[V\setminus S]$ contains no knot. In this paper we focus on graph width measure parameterizations for {\sc KFVD}. First, we show that: (i) {\sc KFVD} parameterized by the size of the solution $k$ is W[1]-hard even when $p$, the length of a longest directed path of the input graph, as well as $\kappa$, its Kenny-width, are bounded by constants, and we remark that {\sc KFVD} is para-NP-hard even considering many directed width measures as parameters, but in FPT when parameterized by clique-width; (ii) {\sc KFVD} can be solved in time $2{O(tw)}\times n$, but assuming ETH it cannot be solved in $2{o(tw)}\times n{O(1)}$, where $tw$ is the treewidth of the underlying undirected graph. Finally, since the size of a minimum directed feedback vertex set ($dfv$) is an upper bound for the size of a minimum knot-free vertex deletion set, we investigate parameterization by $dfv$ and we show that (iii) {\sc KFVD} can be solved in FPT-time parameterized by either $dfv+\kappa$ or $dfv+p$; and it admits a Turing kernel by the distance to a DAG having an Hamiltonian path.
Collections
Sign up for free to add this paper to one or more collections.
Paper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.