Conditional Diagnosability of Augmented Cubes under the PMC Model

Abstract

Processor fault diagnosis has played an important role in measuring the reliability of a multiprocessor system, and the diagnosability of many well-known multiprocessor systems has been widely investigated. The conditional diagnosability is a novel measure of diagnosability by adding an additional condition that any faulty set cannot contain all the neighbors of any node in a system. In this paper, we evaluate the conditional diagnosability for augmented cubes under the PMC model. We show that the conditional diagnosability of an n-dimensional augmented cube is 8n - 27 for n≥5.