Analysis of conditional diagnosability for balanced hypercubes

Abstract

Fault diagnosis plays an important role in ensuring the reliability of a massive multiprocessor system. The identified faulty processors (nodes) of a diagnosed system will be replaced by fault-free nodes. A measure, called diagnosability, of a system is the maximum number of faulty nodes guaranteed to be identified during the diagnosis process. A new measure for fault diagnosis of a system, namely conditional diagnosability, was proposed to improve the number of identified faulty nodes. In this paper, we study the conditional diagnosability of balanced hypercubes under the PMC model and show that the conditional diagnosability of the n-dimensional balanced hypercube is 4n-3 for n ≥ 1.