Research Article
A Matrix Model to Analyze Cascading Failure in Critical Infrastructures
@INPROCEEDINGS{10.1007/978-3-030-51051-0_15, author={Assane Gueye and Babacar Mbaye and Doudou Fall and Alassane Diop and Shigeru Kashihara}, title={A Matrix Model to Analyze Cascading Failure in Critical Infrastructures}, proceedings={Innovations and Interdisciplinary Solutions for Underserved Areas. 4th EAI International Conference, InterSol 2020, Nairobi, Kenya, March 8-9, 2020, Proceedings}, proceedings_a={INTERSOL}, year={2020}, month={8}, keywords={Critical infrastructure Interdependent networks Cascading failures Graph theory Adjacency matrix}, doi={10.1007/978-3-030-51051-0_15} }- Assane Gueye
Babacar Mbaye
Doudou Fall
Alassane Diop
Shigeru Kashihara
Year: 2020
A Matrix Model to Analyze Cascading Failure in Critical Infrastructures
INTERSOL
Springer
DOI: 10.1007/978-3-030-51051-0_15
Abstract
Critical infrastructures are defined as systems and assets, whether physical or virtual, so vital to the nation that their incapacity or destruction would have a debilitating impact on the nation’s existence. Although composed of systems that are usually designed/implementedindependently, critical infrastructures are in realityinterdependent: hence risks/failures will oftencascadefrom one system to another. In this paper, we derive an efficient procedure to fully describe the cascading effects of a node failure in a network of interdependent systems. The procedure is solely based on operations on the adjacency matrix of graph representing the network. We have also shown that the analysis of the cascades can be based on a much smaller matrix that has a DAG structure. This matrix characterization of the cascade and the dimension reduction of the analysis open new opportunities in the study of cascading effects in interdependent networks. Although this paper focuses on the interdependence between the power grid and the communication system, the model presented herein easily generalizes to the interdependence of an arbitrary number of networks.
