The Complexity of Temporal Vertex Cover in Small-Degree Graphs

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 Delta-TVC for time-windows of a fixed-length Delta) 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 Delta-TVC on sparse graphs. Our main result shows that for every Delta geq 2, Delta-TVC is NP-hard 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 Delta-TVC and TVC for which we provide a polynomial-time 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 small-sized temporal vertex cover.

Maximizing Influence Spread through a Dynamic Social Network (Student Abstract)

“…It is worth mentioning that the generalisation of fundamental problems from AI, ML, and computer science to more dynamic settings have occupied the attention of both theorists and practitioners in the last years; to name at least a few, see, e.g., recent works of Hamm et al (2022); Deligkas and Potapov (2020); Mertzios, Molter, and Zamaraev (2019) and the references therein.…”