论文标题
贝叶斯的方法，用于从级联失败中重建相互依存的基础架构网络
A Bayesian Approach to Reconstructing Interdependent Infrastructure Networks from Cascading Failures
论文作者
论文摘要
分析复杂的相互依存网络的行为需要有关网络拓扑以及跨网络的相互依赖链接的完整信息。对于许多应用程序，例如关键基础架构系统，了解网络相互依存对于预测级联故障和计划中断至关重要。但是，由于隐私和安全问题，有关单个网络拓扑的数据通常无法公开使用。另外，相互依存的链接通常仅在级联故障导致的破坏后才揭示。我们提出了一种可扩展的非参数贝叶斯方法，以通过观察级联故障的观察来重建相互依存的基础设施网络的拓扑。采用基础设施依赖性建议的大都市杂货算法来提高抽样可能的图效率。重建相互依存的基础架构网络合成系统的结果表明，所提出的方法在准确性和计算时间上都优于现有方法。我们进一步应用这种方法来重建一个相互依存的基础设施网络的一个合成和两个现实世界系统的拓扑，包括美国田纳西州谢尔比县的加油站 - 水网络以及意大利的相互依存的电力水网络系统，以证明该方法的一般适用性。
Analyzing the behavior of complex interdependent networks requires complete information about the network topology and the interdependent links across networks. For many applications such as critical infrastructure systems, understanding network interdependencies is crucial to anticipate cascading failures and plan for disruptions. However, data on the topology of individual networks are often publicly unavailable due to privacy and security concerns. Additionally, interdependent links are often only revealed in the aftermath of a disruption as a result of cascading failures. We propose a scalable nonparametric Bayesian approach to reconstruct the topology of interdependent infrastructure networks from observations of cascading failures. Metropolis-Hastings algorithm coupled with the infrastructure-dependent proposal are employed to increase the efficiency of sampling possible graphs. Results of reconstructing a synthetic system of interdependent infrastructure networks demonstrate that the proposed approach outperforms existing methods in both accuracy and computational time. We further apply this approach to reconstruct the topology of one synthetic and two real-world systems of interdependent infrastructure networks, including gas-power-water networks in Shelby County, TN, USA, and an interdependent system of power-water networks in Italy, to demonstrate the general applicability of the approach.
