Characterizing optimal monitoring edge-geodetic sets for some structured graph classes
Florent Foucaud, Arti Pandey, Kaustav Paul
TL;DR
This work advances the study of the MIN-MEG problem by providing polynomial-time algorithms for computing meg(G) on several structured graph classes. It centers on the structure of mandatory vertices and its relation to cut-vertices, establishing exact characterizations such as Man(G)=V\setminus Cut(G) for distance-hereditary and bipartite permutation graphs, and meg(G)=|Man(G)| for $P_4$-sparse and strongly chordal graphs. The proofs combine one-vertex-extension orderings, strong elimination orderings, and spider-based decompositions, yielding constructive polynomial-time solutions. These results extend prior tractable cases (e.g., interval graphs, cographs) and deepen understanding of when MEG can be efficiently computed, with implications for network monitoring tasks.
Abstract
Given a graph $G=(V,E)$, a set $S\subseteq V$ is said to be a monitoring edge-geodetic set if the deletion of any edge in the graph results in a change in the distance between at least one pair of vertices in $S$. The minimum size of such a set in $G$ is called the monitoring edge-geodetic number of $G$ and is denoted by $meg(G)$. In this work, we compute the monitoring edge-geodetic number efficiently for the following graph classes: distance-hereditary graphs, $P_4$-sparse graphs, bipartite permutation graphs, and strongly chordal graphs. The algorithms follow from structural characterizations of the optimal monitoring edge-geodetic sets for these graph classes in terms of \emph{mandatory vertices} (those that need to be in every solution). This extends previous results from the literature for cographs, interval graphs and block graphs.
