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The Aftermath of Broken Links: Resilience of IoT Systems from a Networking Perspective

机译:链接断开的后果:从网络角度看物联网系统的弹性

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Internet of things (IoT) is expected to provide a fully informative and controllable environment that features networking, automation, and intelligence by interconnecting physical systems to cyber world. Such a correlation opens the interdependence between the two, upon which a single incident in one domain, e.g., a broken communication link, or an out-of-battery device, can cause a cascade-of-failures across physical and cyber domains. To understand the resilience of IoT systems against such detrimental cascades, this paper studies the aftermath of edge and jointly-induced cascades, that is, a sequence of failures induced by randomly broken physical links (and simultaneous failing cyber nodes) by answering how many nodes will survive the cascade with a newly defined node yield metric. Specifically, we construct a framework to establish self-consistent equations of node yield through an auxiliary graph, without requiring the exact network topology. Then two algorithms are proposed to numerically calculate node yield for interdependent networks with arbitrary degree distributions. For random graph with Poisson degree distributions, we prove the existence of a critical initial edge disconnecting probability φ
机译:物联网(IoT)有望通过将物理系统与网络世界互连来提供具有网络,自动化和智能功能的完全信息化且可控的环境。这种相关关系打开了两者之间的相互依存关系,一个域中的单个事件(例如通信链路断开或电池电量不足)会在物理和网络域上引发一系列故障。为了了解物联网系统对这种有害级联的弹性,本文研究了边缘级联联合级联的后果,即由随机断开的物理链路(以及同时发生故障的网络节点)导致的一系列故障,通过回答多少个节点将使用新定义的节点产量指标在级联中幸存。具体来说,我们构建了一个框架,可通过辅助图建立节点产量的自洽方程,而无需确切的网络拓扑。然后,提出了两种算法对具有任意程度分布的相互依赖的网络进行数值计算。对于具有Poisson度分布的随机图,我们证明存在临界初始边缘断开概率φ

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