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Strongly Diagnosable Product Networks Under the Comparison Diagnosis Model
June 2008 (vol. 57 no. 6)
pp. 721-732
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.

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Index Terms:
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
Citation:
Sun-Yuan Hsieh, Yu-Shu Chen, "Strongly Diagnosable Product Networks Under the Comparison Diagnosis Model," IEEE Transactions on Computers, vol. 57, no. 6, pp. 721-732, June 2008, doi:10.1109/TC.2008.30
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