遭受持续随机攻击的动态网络寿命预测
Predicting Lifetime of Dynamical Networks Experiencing Persistent Random Attacks
摘要：
对复杂系统从一种状态突然翻转到另一种状态的临界点的经验估计是网络科学中剩余的挑战之一。然而，由于临界转变的随机性，人们普遍认为临界点很难估计，甚至更难预测这种转变发生的时间[1-4]。我们分析了一类经历持续攻击的衰减动态网络，其中攻击的大小由内部故障的概率来量化，并且内部故障有可能是永久性的。当活跃邻居的比例下降到临界阈值时，级联故障触发网络崩溃。对于这类网络，我们发现无论是数字和分析，网络崩溃的时间，相当于网络的生命周期，是反向依赖于攻击的大小和grammically依赖于阈值。我们分析了永久性攻击如何影响动态网络的鲁棒性，并使用网络生命周期作为衡量动态网络鲁棒性的一个指标，为系统动力学提供了新的方法论见解。
英文摘要：
Empirical estimation of critical points at which complex systems abruptly flip from one state to another is among the remaining challenges in network science. However, due to the stochastic nature of critical transitions it is widely believed that critical points are difficult to estimate, and it is even more difficult, if not impossible, to predict the time such transitions occur [1-4]. We analyze a class of decaying dynamical networks experiencing persistent attacks in which the magnitude of the attack is quantified by the probability of an internal failure, and there is some chance that an internal failure will be permanent. When the fraction of active neighbors declines to a critical threshold, cascading failures trigger a network breakdown. For this class of network we find both numerically and analytically that the time to the network breakdown, equivalent to the network lifetime, is inversely dependent upon the magnitude of the attack and logarithmically dependent on the threshold. We analyze how permanent attacks affect dynamical network robustness and use the network lifetime as a measure of dynamical network robustness offering new methodological insight into system dynamics.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
