Corrigendum to "Degree-Based Approximations for Network Reliability Polynomials". Comment on J. Complex Networks 2025, 13, cnaf001
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| Natura: | Preprint |
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2025
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| _version_ | 1866916995860004864 |
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| author | Liu, Xinhan Van Mieghem, Piet |
| author_facet | Liu, Xinhan Van Mieghem, Piet |
| contents | Our original paper \cite{VanMieghem2025} described the stochastic approximation $\overline{rel}_G(p)=\bigl[1-ϕ_D(1-p)\bigr]^{N}$ in \cite[eq. (2.2)]{VanMieghem2025} and the first-order approximation $(R_1)_G(p)=\prod_{i=1}^{N}\!\bigl[1-(1-p)^{d_i}\bigr]$ in \cite[eq. (4.1)]{VanMieghem2025} as upper bounds for the all-terminal reliability polynomial \(rel_G(p)\). The present corrigendum clarifies that the unique upper bound is \(\Pr[\hat D_{\min}\geq 1]\), which is difficult to compute exactly, because we must account for correlated node-isolation events. Both the stochastic approximation $\overline{rel}_G$ and the first-order approximation $(R_1)_G$ ignore those correlations, assume independence and, consequently, do not always upperbound \(rel_G(p)\) as stated previously. The complete graph \(K_{3}\) is a counterexample, where both approximations lie below the exact reliability polynomial $rel_{K_3}(p)$, illustrating that they are not upper bounds. Moreover, as claimed in \cite{VanMieghem2025}, the first-order approximation $(R_1)_G$ is not always more accurate than the stochastic approximation $\overline{rel}_G$. We show by an example that the relative accuracy of the stochastic approximation $\overline{rel}_G$ and the first-order approximation $(R_1)_G$ varies with the graph $G$ and the link operational probability $p$. }{network robustness, node failure, probabilistic graph, reliability polynomial |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_06247 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Corrigendum to "Degree-Based Approximations for Network Reliability Polynomials". Comment on J. Complex Networks 2025, 13, cnaf001 Liu, Xinhan Van Mieghem, Piet Physics and Society Applied Physics Our original paper \cite{VanMieghem2025} described the stochastic approximation $\overline{rel}_G(p)=\bigl[1-ϕ_D(1-p)\bigr]^{N}$ in \cite[eq. (2.2)]{VanMieghem2025} and the first-order approximation $(R_1)_G(p)=\prod_{i=1}^{N}\!\bigl[1-(1-p)^{d_i}\bigr]$ in \cite[eq. (4.1)]{VanMieghem2025} as upper bounds for the all-terminal reliability polynomial \(rel_G(p)\). The present corrigendum clarifies that the unique upper bound is \(\Pr[\hat D_{\min}\geq 1]\), which is difficult to compute exactly, because we must account for correlated node-isolation events. Both the stochastic approximation $\overline{rel}_G$ and the first-order approximation $(R_1)_G$ ignore those correlations, assume independence and, consequently, do not always upperbound \(rel_G(p)\) as stated previously. The complete graph \(K_{3}\) is a counterexample, where both approximations lie below the exact reliability polynomial $rel_{K_3}(p)$, illustrating that they are not upper bounds. Moreover, as claimed in \cite{VanMieghem2025}, the first-order approximation $(R_1)_G$ is not always more accurate than the stochastic approximation $\overline{rel}_G$. We show by an example that the relative accuracy of the stochastic approximation $\overline{rel}_G$ and the first-order approximation $(R_1)_G$ varies with the graph $G$ and the link operational probability $p$. }{network robustness, node failure, probabilistic graph, reliability polynomial |
| title | Corrigendum to "Degree-Based Approximations for Network Reliability Polynomials". Comment on J. Complex Networks 2025, 13, cnaf001 |
| topic | Physics and Society Applied Physics |
| url | https://arxiv.org/abs/2510.06247 |