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Network recovery based on system crash early warning in a cascading failure model

机译:级联故障模型中基于系统崩溃预警的网络恢复

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摘要

This paper investigates the possibility of saving a network that is predicted to have a cascading failure that will eventually lead to a total collapse. We model cascading failures using the recently proposed KQ model. Then predict an impending total collapse by monitoring critical slowing down indicators and subsequently attempt to prevent the total collapse of the network by adding new nodes. To this end, we systematically evaluate five node addition rules, the effect of intervention delay and network degree heterogeneity. Surprisingly, unlike for random homogeneous networks, we find that a delayed intervention is preferred for saving scale free networks. We also find that for homogeneous networks, the best strategy is to wire newly added nodes to existing nodes in a uniformly random manner. For heterogeneous networks, however, a random selection of nodes based on their degree mostly outperforms a uniform random selection. These results provide new insights into restoring networks by adding nodes after observing early warnings of an impending complete breakdown.
机译:本文研究了保存可能会级联失败并最终导致完全崩溃的网络的可能性。我们使用最近提出的KQ模型对级联故障建模。然后,通过监视关键的减速指标来预测即将发生的总崩溃,并随后尝试通过添加新节点来防止网络的总崩溃。为此,我们系统地评估了五个节点添加规则,干预延迟的影响和网络度异质性。令人惊讶的是,与随机同构网络不同,我们发现延迟干预是节省无标度网络的首选方法。我们还发现,对于同构网络,最佳策略是以统一随机的方式将新添加的节点连接到现有节点。但是,对于异构网络,基于节点的程度的随机选择通常要优于统一的随机选择。这些结果通过在观察到即将发生完全故障的预警之后添加节点,为恢复网络提供了新的见解。

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