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The t/k-Diagnosability and a t/k Diagnosis Algorithm of the Data Center Network BCCC under the MM* Model.
- Source :
-
Algorithms . Dec2022, Vol. 15 Issue 12, p480. 16p. - Publication Year :
- 2022
-
Abstract
- The evaluation of the fault diagnosis capability of a data center network (DCN) is important research in measuring network reliability. The g-extra diagnosability is defined under the condition that every component except the fault vertex set contains at least g+1 vertices. The t/k diagnosis strategy is that the number of fault nodes does not exceed t, and all fault nodes can be isolated into a set containing up to k fault-free nodes. As an important data center network, BCube Connected Crossbars (BCCC) has many excellent properties that have been widely studied. In this paper, we first determine that the g-extra connectivity of B C n , k for 0 ≤ g ≤ n − 1 . Based on this, we establish the g-extra conditional diagnosability of B C n , k under the MM* model for 1 ≤ g ≤ n − 1 . Next, based on the conclusion of the largest connected component in g-extra connectivity, we prove that the t/k-diagnosability of B C n , k under the MM* model for 1 ≤ k ≤ n − 1 . Finally, we present a t/k diagnosis algorithm on BCCC under the MM* model. The algorithm can correctly identify all nodes at most k nodes undiagnosed. So far, t/k-diagnosability and diagnosis algorithms for most networks in the MM* model have not been studied. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 19994893
- Volume :
- 15
- Issue :
- 12
- Database :
- Academic Search Index
- Journal :
- Algorithms
- Publication Type :
- Academic Journal
- Accession number :
- 160940194
- Full Text :
- https://doi.org/10.3390/a15120480