t/k-fault diagnosis algorithm of n-dimensional hypercube network based on the MM∗ model

Compared with accurate diagnosis, the system's self-diagnosing capability can be greatly increased through the t/k-diagnosis strategy at most k vertexes to be mistakenly identified as faulty under the comparison model, where k is typically a small number. Based on the Preparata, Metze, and Chien (PMC) model, the n-dimensional hypercube network is proved to be t/k-diagnosable. In this paper, based on the Maeng and Malek (MM)* model, a novel t/k-fault diagnosis (1 ≤ k ≤ 4) algorithm of n-dimensional hypercube, called t/k-MM*-DIAG, is proposed to isolate all faulty processors within the set of nodes, among which the number of fault-free nodes identified wrongly as faulty is at most k. The time complexity in our algorithm is only O(2ⁿn²).