Monitoring edge-geodetic sets in graphs

TL;DR

This paper introduces the concept of monitoring edge-geodetic sets (MEG-sets) in graphs for network failure detection, analyzes their minimum size in various graph classes, and proves the problem's NP-hardness.

Contribution

It defines MEG-sets, explores their properties in different graph classes, and establishes NP-hardness of finding minimum MEG-sets.

Findings

Minimum MEG-set sizes for trees, cycles, and other classes

Upper bounds using feedback edge sets

NP-hardness of the problem

Abstract

We introduce a new graph-theoretic concept in the area of network monitoring. In this area, one wishes to monitor the vertices and/or the edges of a network (viewed as a graph) in order to detect and prevent failures. Inspired by two notions studied in the literature (edge-geodetic sets and distance-edge-monitoring sets), we define the notion of a monitoring edge-geodetic set (MEG-set for short) of a graph $G$ as an edge-geodetic set $S\subseteq V(G)$ of $G$ (that is, every edge of $G$ lies on some shortest path between two vertices of $S$) with the additional property that for every edge $e$ of $G$, there is a vertex pair $x, y$ of $S$ such that $e$ lies on all shortest paths between $x$ and $y$. The motivation is that, if some edge $e$ is removed from the network (for example if it ceases to function), the monitoring probes $x$ and $y$ will detect the failure since the distance between them will increase. We explore the notion of MEG-sets by deriving the minimum size of a MEG-set for some basic graph classes (trees, cycles, unicyclic graphs, complete graphs, grids, hypercubes, corona products...) and we prove an upper bound using the feedback edge set of the graph. We also show that determining the smallest size of an MEG-set of a graph is NP-hard, even for graphs of maximum degree at most~9.