Prevention and Mitigation of Catastrophic Failures in Demand-Supply Interdependent Networks
Prevention and Mitigation of Catastrophic Failures in Demand-Supply Interdependent Networks
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DOI：
10.1109/tnse.2019.2951084
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发表时间：
2020-07-01
影响因子：
6.6
通讯作者：
Dai, Huaiyu
中科院分区：
文献类型：
--
作者：
Hosseinalipour, Seyyedali;Mao, Jiayu;Dai, Huaiyu
我们提出了一个通用的系统模型的一个特殊类别的相互依赖的网络，需求-供应网络，其中的需求和供应节点与异构的负载和资源，分别。我们的模型揭示了一个独特的级联故障机制引起的资源/负载波动，这反过来又打开了大门，相互依赖的网络进行压力分析。与现有的文献主要关注节点的连通性相比，我们专注于开发有效的资源分配方法，以防止这些级联故障的发生，并减轻/限制它们发生在网络中。为了防止级联故障，我们确定了一些危险的压力机制，在此基础上，我们量化的资源配置方案方面的网络的鲁棒性。之后，我们确定两个资源/负载波动的情况下的最佳资源配置：均匀和成比例的波动。我们进一步研究了考虑异构资源共享成本的最优资源配置问题。为了缓解/限制持续的级联故障，我们提出了两种网络自适应机制：故意故障和资源重新调整，在此基础上，我们提出了一种算法，以减轻正在进行的级联故障，同时加强幸存的网络具有高鲁棒性，以避免进一步的故障。
We propose a generic system model for a special category of interdependent networks, demand-supply networks, in which the demand and the supply nodes are associated with heterogeneous loads and resources, respectively. Our model sheds a light on a unique cascading failure mechanism induced by resource/load fluctuations, which in turn opens the door to conducting stress analysis on interdependent networks. Compared to the existing literature mainly concerned with the node connectivity, we focus on developing effective resource allocation methods to prevent these cascading failures from happening and to mitigate/confine them upon occurrence in the network. To prevent cascading failures, we identify some dangerous stress mechanisms, based on which we quantify the robustness of the network in terms of the resource configuration scheme. Afterward, we identify the optimal resource configuration under two resource/load fluctuations scenarios: uniform and proportional fluctuations. We further investigate the optimal resource configuration problem considering heterogeneous resource sharing costs among the nodes. To mitigate/confine ongoing cascading failures, we propose two network adaptations mechanisms: intentional failure and resource re-adjustment, based on which we propose an algorithm to mitigate an ongoing cascading failure while reinforcing the surviving network with a high robustness to avoid further failures.