The DOI matches its Crossref record.
Network resilience: a measure of network fault tolerance
Abstract
A probabilistic measure of network fault tolerance expressed as the probability of a disconnection is proposed. Qualitative evaluation of this measure is presented. As expected, the single-node disconnection probability is the dominant factor irrespective of the topology under consideration. The authors derive an analytical approximation to the disconnection probability and verify it with a Monte Carlo simulation. On the basis of this model, the measures of network resilience and relative network resilience are proposed as probabilistic measures of network fault tolerance. These are used to evaluate the effects of the disconnection probability on the reliability of the system.>
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Towards a Conceptual Framework for Resilience Engineering
Madni, A. M., & Jackson, S. (2009) · IEEE Systems Journal · doi:10.1109/jsyst.2009.2017397 · Cited by 649
Challenges in the vulnerability and risk analysis of critical infrastructures
Zio, E. (2016) · Reliability Engineering & System Safety · doi:10.1016/j.ress.2016.02.009 · Cited by 429
Zio, E. (2018) · Reliability Engineering & System Safety · doi:10.1016/j.ress.2018.04.020 · Cited by 401
Beyond Adaptation: Resilience for Business in Light of Climate Change and Weather Extremes
Linnenluecke, M., & Griffiths, A. (2010) · Business & Society · doi:10.1177/0007650310368814 · Cited by 386
Metadata
- Authors
- Najjar, W., & Gaudiot, J.-L.
- Venue
- IEEE Transactions on Computers
- Published
- 1990
- Volume
- 39
- Issue
- 2
- Pages
- 174-181
- ISSN
- 0018-9340 (ISSN-L)
- OpenAlex
- W2156804553
- Cited by
- 207
- References
- 0
- FWCI
- 15.49
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Network resilience: a measure of network fault tolerance. https://app.cochat.ai/papers/10.1109/12.45203
- The paper
- Najjar, W., & Gaudiot, J.-L. (1990). Network resilience: a measure of network fault tolerance. IEEE Transactions on Computers. https://doi.org/10.1109/12.45203
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
