Search arXivSearch

arXiv · 2607.23155

Eternal Vertex Cover Problem on Halin Graphs

Abstract

Eternal vertex cover problem is a graph protection problem which is a dynamic two player game variant of the classical vertex cover problem. In this game, the minimum number of guards required to protect a graph $G$ is called the eternal vertex cover number of $G$, denoted by $evc(G)$. It is known that for any graph $G$, $\ mvc(G) \le evc(G) \le 2mvc(G)$, where $mvc(G)$ is the vertex cover number of $G$, and that these bounds are generally tight. However, no biconnected graph $G$ achieves $evc(G) = 2mvc(G)$ and no better lower bounds are known for them. In this work, we focus on biconnected graphs in graph families. For infinite graph families $\mathcal{F}$, consider the parameter $ρ(\mathcal{F})=\sup\{r \in \mathbb{R}:\text{ for infinitely many graphs }G \in \mathcal{F},\frac{evc(G)}{mvc(G)}\ge r\}$. No class of biconnected graphs $\mathcal{F}$ is known yet, for which $1 < ρ(\mathcal{F})<2$. In this paper, we show that when $\mathcal{F}$ is the family of Halin graphs, $\frac{7}{6} \le ρ(\mathcal{F}) \le \frac{3}{2}$. Halin graphs are $3$-connected and they have treewidth three. To show the lower bound, we construct a family of Halin graphs for which the ratio tends to $\frac{7}{6}$ with increasing graph size. For the upper bound, we give two algorithms. Our first algorithm gives a defense strategy with $\frac{3}{2} mvc(G)$ guards and serves as a $\frac{3}{2}$ factor approximation algorithm to compute the eternal vertex cover number of Halin graphs. This algorithm also gives an upper bound of $\frac{4}{3}$ for $ρ$ for several subclasses of Halin graphs. Our second algorithm attains the upper bound of $\frac{4}{3}$ for caterpillar Halin graphs. Whether computing eternal vertex cover number is NP-hard for Halin graphs remains an open problem, as is the case with treewidth two graphs.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Jasine Babu, Pratik Ghosal, Cipriyano Simoes. 2026-07-25. Eternal Vertex Cover Problem on Halin Graphs. https://arxiv.org/abs/2607.23155

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Flip Dynamics for Sampling Colorings: Improving $(11/6-ε)$ Using a Simple Metric

We present improved bounds for randomly sampling $k$-colorings of graphs with maximum degree $Δ$; our results hold without any further structural assumptions on the graph. The Glauber dynamics is a simple single-site update Markov chain. Jerrum (1995) proved an optimal $O(n\log{n})$ mixing-time bound for Glauber dynamics whenever $k>2Δ$ where $Δ$ is the maximum degree of the input graph. This bound was improved by Vigoda (1999) to $k>(11/6)Δ$ using a "flip" dynamics which recolors (small) maximal two-colored components in each step. Vigoda's result was the best known for general graphs for 20 years until Chen et al. (2019) established optimal mixing of the flip dynamics for $k>(11/6-\varepsilon)Δ$ where $\varepsilon\approx 10^{-5}$. We present the first substantial improvement over these results. We prove an optimal mixing-time bound of $O(n\log{n})$ for the flip dynamics when $Δ\geq125$ and $k\geq1.809Δ$. This yields, through recent spectral independence results, an optimal $O(n\log{n})$ mixing time for the Glauber dynamics for every fixed $Δ\geq125$ in the same range of $k/Δ$. Our proof utilizes path coupling with a simple weighted Hamming distance for "unblocked" neighbors.

cs.DM

Factorisability of Low Dimensional Non-Negative Integer Matrices

We consider the problem of determining if a given two-dimensional nonnegative integer matrix $M$ is the product of two such matrices, excluding trivial units. A matrix $M$ with no such factorisation is called prime and therefore belongs to the minimal (infinite rank) generator of $2 \times 2$ matrices over the natural numbers, otherwise it is called composite. We also consider the problem of finding a (non-unique) factorisation of a composite matrix. Our results have applications in computational group theory and the theory of codes, where such matrices are called incidence matrices. We analyse the complexity of primality and finding a factorisation for a composite matrix, providing a first efficient algorithm.

cs.DM