The Conditional Diagnosability of Twisted Cubes under the Comparison Model

Abstract

In evaluating the fault tolerance of an network structure, it is essential to estimate the order of a maximal connected component of this network provided the faulty vertices may break its connectedness, and it is crucial to local and to replace the faulty processors to maintain system’s high reliability. The fault diagnosis is the process of identifying fault processors in a system through testing. The conditional diagnosis requires that for each processor v in a system, all the processors that are directly connected to v do not fail at the same time. In this paper, the conditional diagnosability of the twisted cubes TQn under the comparison diagnosis model is 3n-5 when n≫6. Hence the conditional diagnosability of TQn is three times larger than its classical diagnosability.