Computational complexity of network vulnerability analysis
Residual closeness is recently proposed as a vulnerability measure to characterize the stability of complex networks. Residual closeness is essential in the analysis of complex networks, but costly to compute. Currently, the fastest known algorithms run in polynomial time. Motivated by the fast-grow...
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Format: | Article |
Language: | English |
Published: |
Sciendo
2022-12-01
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Series: | Acta Universitatis Sapientiae: Informatica |
Subjects: | |
Online Access: | https://doi.org/10.2478/ausi-2022-0012 |
Summary: | Residual closeness is recently proposed as a vulnerability measure to characterize the stability of complex networks. Residual closeness is essential in the analysis of complex networks, but costly to compute. Currently, the fastest known algorithms run in polynomial time. Motivated by the fast-growing need to compute vulnerability measures on complex networks, new algorithms for computing node and edge residual closeness are introduced in this paper. Those proposed algorithms reduce the running times to Θ(n3) and Θ (n4) on unweighted networks, respectively, where n is the number of nodes. |
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ISSN: | 2066-7760 |