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The study of real-world communication systems via complex network models has greatly expanded the people understanding on how information flows, even in completely decentralized architectures such as mobile wireless networks. Nonetheless, static network models cannot capture the time-varying aspects and, therefore, various temporal metrics have been introduced. In this paper, the authors investigate the robustness of time-varying networks under various failures and intelligent attacks. They adopt a methodology to evaluate the impact of such events on the network connectivity by employing temporal metrics in order to select and remove nodes based on how critical they are considered for the network. They also define the temporal robustness range, a new metric that quantifies the disruption caused by an attack strategy to a given temporal network.
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