Conditional diagnosability of matching composition networks under the MM* model
Information Sciences: an International Journal
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The growing size of the multiprocessor systems increases their vulnerability to component failures. It is crucial to locate and replace the faulty processors to maintain the system's high reliability. The fault diagnosis is the process of identifying faulty 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 simultaneously. In this paper, we show that the conditional diagnosability of the crossed cubes CQn under the comparison diagnosis model is 3n-5 when n≥7. Hence, the conditional diagnosability of CQn is three times larger than its classical diagnosability.