Abstract
We study the problem of identifying nodes that are more likely to trigger cascading failures in complex systems, which we call vulnerable nodes. We show that there is a close relation between the likelihood of a node setting off cascading failures (which we call the cascading failure probability) and its non-backtracking centrality; when every failed node is equally likely to cause the failure of each neighbor, the cascading failure probability and non-backtracking centrality of a node are proportional to each other. Based on this observation, we propose a new approach to finding vulnerable nodes and study its performance using numerical studies.
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Notes
- 1.
These dependence relations are not necessarily the physical links in a network. For example, in a power system, an overload failure in one part of power grid can cause a failure in another part that is not geographically close or without direct physical connection to the former.
- 2.
It is shown that the degree distribution of many real networks can be approximated using a power law [1].
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Acknowledgement
This work was supported in part by contract 70NANB16H024 from National Institute of Standards and Technology (NIST).
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La, R.J. (2019). Identifying Vulnerable Nodes to Cascading Failures: Centrality to the Rescue. In: Aiello, L., Cherifi, C., Cherifi, H., Lambiotte, R., Lió, P., Rocha, L. (eds) Complex Networks and Their Applications VII. COMPLEX NETWORKS 2018. Studies in Computational Intelligence, vol 812. Springer, Cham. https://doi.org/10.1007/978-3-030-05411-3_69
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DOI: https://doi.org/10.1007/978-3-030-05411-3_69
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