Conditional diagnosability of matching composition networks under the MM∗ model

Diagnosability is a critical metric for determining the reliability of a multiprocessor system. In 2005, Lai et al. proposed a new measure for the fault diagnosis of a system, i.e., conditional diagnosability, in which it is assumed that at least one of the neighbors of an arbitrary node in the system is not faulty. In this paper, we obtain a sufficient condition for a class of networks, called Matching Composition Networks (MCNs), which are conditionally t-diagnosable under the MM∗ model. Then, we apply the sufficient condition to show the conditional diagnosability of bijective connection (BC) networks. Finally, we show that the sufficient condition can be applied to networks other than BC networks.