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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 $t$-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.
Reliability, Testing, and Fault-Tolerance, Fault tolerance, Measurement, evaluation, modeling, simulation of multiple-processor systems, On-chip interconnection networks, Graph Theory, Discrete Mathematics, Mathematics of Computing, Network problems, Graph Theory, Discrete Mathematics, Mathematics of Computing

S. Hsieh and Y. Chen, "Strongly Diagnosable Product Networks Under the Comparison Diagnosis Model," in IEEE Transactions on Computers, vol. 57, no. , pp. 721-732, 2008.
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