cascading failures
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2022 ◽  
Vol 217 ◽  
pp. 108068
Author(s):  
Hao Liu ◽  
Xin Chen ◽  
Long Huo ◽  
Yadong Zhang ◽  
Chunming Niu

2021 ◽  
Vol 153 ◽  
pp. 111460
Author(s):  
Mattia Frasca ◽  
Lucia Valentina Gambuzza

Author(s):  
Guixiang Lv ◽  
Liudong Xing

During the coronavirus pandemic, telecommuting is widely required, making remote data access grow significantly. This requires highly reliable data storage solutions. Storage area networks (SANs) are one of such solutions. To guarantee that SANs can deliver the desired quality of service, cascading failures must be prevented, which occur when a single initial incident triggers a cascade of unexpected failures of other devices. One such incident is the data loading/overloading, causing the malfunction of one device and further cascading failures. Thus, it is crucial to address influence of data loading on the SAN reliability modeling and analysis. In this work, we make contributions by modeling the effects of data loading on the reliability of an individual switch device in SANs though the proportional-hazards model and accelerated failure-time model. Effects of loading on the reliability of the entire SAN are further investigated through dynamic fault trees and binary decision diagrams-based analysis of a mesh SAN system.


2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Huiqiong Deng ◽  
Junyuan Wu ◽  
Jie Luo ◽  
Renwu Yan ◽  
Cheng Zhang ◽  
...  

The practical application of wireless sensor networks (WSNs) in hot fields is summarized. It is found that compared with traditional monitoring methods, it has better adaptability to complex environments and low cost. It is suitable for monitoring power grid operation parameters. Therefore, this paper combines the above network and cascading failures, analyzes its 24-hour continuous and dynamic monitoring of the operation parameters of the power grid, and considers how to use the obtained parameters to analyze the disturbance of the remaining lines after the initial fault of the power grid. To prevent cascading failures in the power grid, a preventive control model considering safety and economy is proposed, and the model is solved by nondominated sorting genetic algorithm II and particle swarm optimization (NSGA2-PSO). Finally, the rationality of this method is verified in the IEEE39 node system.


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