Abstract
A resolving set R in a graph G is a set of vertices such that every vertex of G is uniquely identified by its distances to the vertices of R. Introduced in the 1970’s, this concept has been since then extensively studied from both combinatorial and algorithmic point of view. We propose a generalization of the concept of resolving sets to temporal graphs, i.e., graphs with edge sets that change over discrete time-steps. In this setting, the temporal distance from u to v is the earliest possible time-step at which a journey with strictly increasing time-steps on edges leaving u reaches v, i.e., the first time-step at which v could receive a message broadcast from u. A temporal resolving set of a temporal graph \(\mathcal {G}\) is a subset R of its vertices such that every vertex of \(\mathcal {G}\) is uniquely identified by its temporal distances from vertices of R. We study the problem of finding a minimum-size temporal resolving set, and show that it is NP-complete even on very restricted graph classes and with strong constraints on the time-steps: temporal complete graphs where every edge appears in either time-step 1 or 2, temporal trees where every edge appears in at most two consecutive time-steps, and even temporal subdivided stars where every edge appears in at most two (not necessarily consecutive) time-steps. On the other hand, we give polynomial-time algorithms for temporal paths and temporal stars where every edge appears in exactly one time-step, and give a combinatorial analysis and algorithms for several temporal graph classes where the edges appear in periodic time-steps.
This work was supported by the International Research Center “Innovation Transportation and Production Systems” of the I-SITE CAP 20-25 and by the ANR project GRALMECO (ANR-21-CE48-0004). Jan Bok was also funded by the European Union (ERC, POCOCOP, 101071674). Tuomo Lehtilä was also supported by Business Finland Project 6GNTF, funding decision 10769/31/2022.
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Bok, J., Dailly, A., Lehtilä, T. (2024). Resolving Sets in Temporal Graphs. In: Rescigno, A.A., Vaccaro, U. (eds) Combinatorial Algorithms. IWOCA 2024. Lecture Notes in Computer Science, vol 14764. Springer, Cham. https://doi.org/10.1007/978-3-031-63021-7_22
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