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Robustness of Interdependent Cyber-Physical Systems Against Cascading Failures

机译:相互依存网络地物理系统对级联故障的鲁棒性

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Integrated cyber-physical systems, such as the smart-grid, are increasingly becoming the underpinning technology for major industries. A major concern regarding such systems are the seemingly unexpected large scale failures, which are often attributed to a small initial shock getting escalated due to intricate dependencies within and across the individual (e.g., cyber and physical) counterparts of the system. In this paper, we develop a novel interdependent system model to capture this phenomenon, also known as cascading failures. Our framework consists of two networks that have inherently different characteristics governing their intradependence: first, a cyber-network where a node is deemed to be functional as long as it belongs to the largest connected (i.e., giant) component; and, second, a physical network where nodes are given an initial flow and a capacity, and failure of a node results with redistribution of its flow to the remaining nodes, upon which further failures might take place due to overloading (i.e., the flow of a node exceeding its capacity). Furthermore, it is assumed that these two networks are interdependent. For simplicity, we consider a one-to-one interdependence model where every node in the cyber-network is dependent upon and supports a single node in the physical network, and vice versa. We provide a thorough analysis of the dynamics of cascading failures in this interdependent system initiated with a random attack. The system robustness is quantified as the surviving fraction of nodes at the end of cascading failures, and is derived in terms of all network parameters involved (e.g., degree distribution, load/capacity distribution, failure size, etc.). Analytic results are supported through an extensive numerical study. Among other things, these results demonstrate the ability of our model to capture the unexpected nature of large-scale failures, and provide insights on improving system robustness.
机译:综合网络系统(如智能电网)越来越多地成为主要产业的支撑技术。关于这种系统的主要问题是看似意外的大规模失败,这些失败通常归因于由于系统内的个人(例如,网络和物理)对应物中的复杂依赖性而升级的小初始冲击。在本文中,我们开发了一种新颖的相互依存系统模型来捕获这种现象,也称为级联故障。我们的框架由两个网络组成,它具有固有的不同特征,其内在的互联器:首先,一个网络网络,其中一个节点被认为是功能的,只要它属于它所属的连接(即,巨头)组件即可;并且,第二,给出节点的物理网络,其中节点被赋予初始流量和容量,并且节点的故障导致其流向其剩余节点的重新分布,在其上可能发生进一步的故障(即,流量)超过其容量的节点)。此外,假设这两个网络是相互依存的。为简单起见,我们考虑一个一对一的相互依存模型,其中网络网络中的每个节点都取决于物理网络中的单个节点,反之亦然。我们对随机攻击启动的这种相互依存系统中的级联故障的动态进行了全面的分析。系统鲁棒性被量化为级联故障结束时节点的幸存分数,并且在涉及的所有网络参数方面导出(例如,度分布,负载/容量分布,故障尺寸等)。通过广泛的数值研究支持分析结果。在其他事情之外,这些结果表明了我们模型捕捉大规模失败意外性的能力,并提供了改善系统稳健性的见解。

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