Strongly Diagnosable Product Networks Under the Comparison Diagnosis Model

The notion of diagnosability has long played an important role in measuring the reliability of multiprocessor systems. Such a system is t-diagnosable if all faulty nodes can be identified without replacement when the number of faults does not exceed t, where t is some positive integer. Furthermore, a system is strongly i-diagnosable if it can achieve (t + 1)-diagnosability, except for the case where a node´s neighbors are all faulty. In this paper, we investigate the strong diagnosability of a class of product networks, under the comparison diagnosis model. Based on our results, we can determine the strong diagnosability of several widely used multiprocessor systems, such as hypercubes, mesh-connected k-ary n-cubes, torus-connected k-ary n-cubes, and hyper-Petersen networks.