A New Sequential Diagnosis Algorithm in Hypercubes with High Diagnosability

Abstract

We consider the problem of sequential fault diagnosis in hypercube multiprocessor system under the PMC model. The diagnosability is defined as the ability to provide a correct and complete diagnosis. In this paper, we proposed a novel and simple sequential diagnosis method called the Major Aggregate (MA) Algorithm. Moreover, the lower bound of diagnosability in our method is proved as a d-dimensional hypercube. This result obviously improves the best lower bound of diagnosability, in previous researches.