Skip to Main content Skip to Navigation
Journal articles

Resilience-based component importance measures for critical infrastructure network systems

Abstract : In this paper, we propose two metrics, i.e. the optimal repair time and the resilience reduction worth, to measure the criticality of the components of a network system from the perspective of their contribution to system resilience. Specifically, the two metrics quantify (i) the priority with which a failed component should be repaired and re-installed into the network, and (ii) the potential loss in the optimal system resilience due to a time delay in the recovery of a failed component, respectively. Given the stochastic nature of disruptive events on infrastructure networks, a Monte Carlo-based method is proposed to generate probability distributions of the two metrics for all the components of the network; then, a stochastic ranking approach based on the Copeland's pairwise aggregation is used to rank components importance. Numerical results are obtained for the IEEE 30 Bus test network and a comparison is made with three classical centrality measures.
Complete list of metadatas

Cited literature [48 references]  Display  Hide  Download

https://hal.archives-ouvertes.fr/hal-01436576
Contributor : Nicola Pedroni <>
Submitted on : Monday, January 16, 2017 - 3:29:15 PM
Last modification on : Friday, October 16, 2020 - 2:21:25 PM
Long-term archiving on: : Monday, April 17, 2017 - 2:47:26 PM

File

Resilience-based CIMs_Revised_...
Files produced by the author(s)

Identifiers

Citation

Yi-Ping Fang, Nicola Pedroni, Enrico Zio. Resilience-based component importance measures for critical infrastructure network systems. IEEE Transactions on Reliability, Institute of Electrical and Electronics Engineers, 2016, 65 (2), pp.502-512. ⟨10.1109/TR.2016.2521761⟩. ⟨hal-01436576v1⟩

Share

Metrics

Record views

232

Files downloads

410