期刊
THEORETICAL COMPUTER SCIENCE
卷 849, 期 -, 页码 197-201出版社
ELSEVIER
DOI: 10.1016/j.tcs.2020.10.023
关键词
R-g-conditional diagnosability; Hypercube; PMC model
资金
- National Natural Science Foundation of China [61977016, 61872257, 61572010]
- Natural Science Foundation of Fujian Province [2020J01164, 2017J01738, JAT170118, JT180077]
The paper discusses the importance of g-good-neighbor conditional diagnosability and R-g-conditional diagnosability in network diagnosis, presenting some conclusions and lower bounds for the corresponding models.
The g-good-neighbor conditional diagnosability, which specifies at least g fault-free neighbors for each fault-free node, is a very important metric in system-level diagnosis. Recently, the g-good-neighbor conditional diagnosabilities of many networks have been investigated. To enhance the g-good-neighbor conditional diagnosability, the R-g-conditional diagnosability, which requires at least g fault-free neighbors for each node, has been proposed by Guo et al. [1] (2020) recently. And they establish the R-g-conditional diagnosability of the hypercubes under the PMC model. In this paper, we present some counterexamples for the proof of lower bound on the R-g-conditional diagnosability of the hypercubes under the PMC model, which is crucial to the original main result. And we further utilize known results to give a reasonable lower bound for the R-g-conditional diagnosability of hypercubes (C) 2020 Elsevier B.V. All rights reserved.
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