In:
ACM Transactions on Design Automation of Electronic Systems, Association for Computing Machinery (ACM), Vol. 28, No. 3 ( 2023-05-31), p. 1-19
Abstract:
The fault diagnosability of a network indicates the self-diagnosis ability of the network, thus it is an important measure of robustness of the network. As a neoteric feature for measuring fault diagnosability, the r -component diagnosability ct r (G) of a network G imposes the restriction that the number of components is at least r in the remaining network of G by deleting faulty set X , which enhances the diagnosability of G . In this article, we establish the r -component diagnosability for n -dimensional hierarchical cubic network HCN n , and we show that, under both PMC model and MM* model, the r -component diagnosability of HCN n is rn -½( r -1) r +1 for n ≥ 2 and 1≤ r≤ n-1 . Moreover, we introduce the concepts of 0-PMC subgraph and 0-MM* subgraph of HCN n . Then, we make use of 0-PMC subgraph and 0-MM* subgraph of HCN n to design two algorithms under PMC model and MM* model, respectively, which are practical and efficient for component fault diagnosis of HCN n . Besides, we compare the r -component diagnosability of HCN n with the extra conditional diagnosability, diagnosability, good-neighbor diagnosability, pessimistic diagnosability, and conditional diagnosability, and we verify that the r -component diagnosability of HCN n is higher than the other types of diagnosability.
Type of Medium:
Online Resource
ISSN:
1084-4309
,
1557-7309
Language:
English
Publisher:
Association for Computing Machinery (ACM)
Publication Date:
2023
detail.hit.zdb_id:
1501152-5
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