Conditional diagnosability of balanced hypercubes under the MMau model

Fault diagnosis plays an important role in ensuring the reliability of a massive multiprocessor system. Diagnosability of a system is the maximum number of faulty nodes guaranteed to be identified during the diagnosis process, and thus is a critical metric to the reliability of the system. To have a greater number of identified faulty nodes, a new measure called conditional diagnosability for fault diagnosis was introduced, which has a normally used assumption. This paper addresses the conditional diagnosability of balanced hypercubes under the MMau model, which is a realistic model to the fault diagnosis of a system. We show that the conditional diagnosability of the n-dimensional balanced hypercube is 4n-4 for na parts per thousand yen2.