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The complexity of temporal vertex cover in small-degree graphs

Hamm, T.; Klobas, N.; Mertzios, G.B.; Spirakis, P.G.

Authors

T. Hamm

Nina Klobas nina.klobas@durham.ac.uk
PGR Student Doctor of Philosophy

P.G. Spirakis



Abstract

Temporal graphs naturally model graphs whose underlying topology changes over time. Recently, the problems Temporal Vertex Cover (or TVC) and Sliding-Window Temporal Vertex Cover (or ∆- TVC for time-windows of a fixed-length ∆) have been established as natural extensions of the classic Vertex Cover problem on static graphs with connections to areas such as surveillance in sensor networks. In this paper we initiate a systematic study of the complexity of TVC and ∆-TVC on sparse graphs. Our main result shows that for every ∆ ≥ 2, ∆-TVC is NPhard even when the underlying topology is described by a path or a cycle. This resolves an open problem from literature and shows a surprising contrast between ∆- TVC and TVC for which we provide a polynomialtime algorithm in the same setting. To circumvent this hardness, we present a number of exact and approximation algorithms for temporal graphs whose underlying topologies are given by a path, that have bounded vertex degree in every time step, or that admit a smallsized temporal vertex cover.

Citation

Hamm, T., Klobas, N., Mertzios, G., & Spirakis, P. (2022). The complexity of temporal vertex cover in small-degree graphs. . https://doi.org/10.1609/aaai.v36i9.21259

Conference Name 36th AAAI Conference on Artificial Intelligence (AAAI 2022)
Conference Location Vancouver, BC
Start Date Feb 22, 2023
End Date Mar 1, 2022
Acceptance Date Dec 2, 2021
Publication Date Jun 28, 2022
Deposit Date Dec 8, 2021
Publisher Association for the Advancement of Artificial Intelligence
Pages 10193-10201
Series Number 9
DOI https://doi.org/10.1609/aaai.v36i9.21259
Keywords Search And Optimization (SO), Planning, Routing, And Scheduling (PRS)