Network decontamination is a well-known problem, in which the aim of the mobile agents should be to decontaminate the network (i.e., both nodes and edges). This problem comes with an added constraint, i.e., of \emph{monotonicity}, in which whenever a node or an edge is decontaminated, it must not get recontaminated. Hence, the name comes \emph{monotone decontamination}. This problem has been relatively explored in static graphs, but nothing is known yet in dynamic graphs. We, in this paper, study the \emph{monotone decontamination} problem in arbitrary dynamic graphs. We designed two models of dynamicity, based on the time within which a disappeared edge must reappear. In each of these two models, we proposed lower bounds as well as upper bounds on the number of agents, required to fully decontaminate the underlying dynamic graph, monotonically. Our results also highlight the difficulties faced due to the sudden disappearance or reappearance of edges. Our aim in this paper has been to primarily optimize the number of agents required to solve monotone decontamination in these dynamic networks.

翻译：网络去污是一个经典问题，其目标是通过移动智能体实现对网络（包括节点与边）的完全去污。该问题附带一项额外约束，即单调性要求：一旦节点或边被去污，便不得再次被污染。因此，该问题被称为单调去污。现有研究在静态图中对此问题已有较多探讨，但在动态图中尚未有相关成果。本文针对任意动态图研究单调去污问题。我们基于消失边重新出现的时间阈值，设计了两种动态性模型。针对每种模型，我们分别提出了在单调约束下完全去污底层动态图所需智能体数量的下界与上界。研究结果同时揭示了边突然消失或重现所带来的复杂性。本文的核心目标在于优化解决此类动态网络中单调去污问题所需智能体的数量。