Temporal Graph Realization With Bounded Stretch
Abstract
A periodic temporal graph, in its simplest form, is a graph in which every edge appears exactly once in the first time steps, and then it reappears recurrently every time steps, where is a given period length. This model offers a natural abstraction of transportation networks where each transportation link connects two destinations periodically. From a network design perspective, a crucial task is to assign the time-labels on the edges in a way that optimizes some criterion. In this paper we introduce a very natural optimality criterion that captures how the temporal distances of all vertex pairs are `stretched', compared to their physical distances, i.e. their distances in the underlying static (non-temporal) graph. Given a static graph , the task is to assign to each edge one time-label between 1 and such that, in the resulting periodic temporal graph with period~, the duration of the fastest temporal path from any vertex to any other vertex is at most times the distance between and in . Here, the value of measures how much the shortest paths are allowed to be \emph{stretched} once we assign the periodic time-labels. Our results span three different directions: First, we provide a series of approximation and NP-hardness results. Second, we provide approximation and fixed-parameter algorithms. Among them, we provide a simple polynomial-time algorithm (the \textit{radius-algorithm}) which always guarantees an approximation strictly smaller than , and which also computes the optimum stretch in some cases. Third, we consider a parameterized local search extension of the problem where we are given the temporal labeling of the graph, but we are allowed to change the time-labels of at most edges; for this problem we prove that it is W[2]-hard but admits an XP algorithm with respect to .
Cite
@article{arxiv.2504.14258,
title = {Temporal Graph Realization With Bounded Stretch},
author = {George B. Mertzios and Hendrik Molter and Nils Morawietz and Paul G. Spirakis},
journal= {arXiv preprint arXiv:2504.14258},
year = {2025}
}