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Conditional Diagnosability of (n; k)-Star Graphs under the PMC Model

Conditional Diagnosability of (n; k)-Star Graphs under the PMC Model

Abstract:

Fault diagnosis has played a major role in measuring the reliability of multiprocessor systems. The diagnosability of many well-known multiprocessor systems has been widely investigated. Conditional diagnosability is a novel property of measuring diagnosability by adding a further condition that any fault set cannot contain all the neighbors of every node in the system. Several known structural properties of (n; k)-star graphs are exhibited. Based on these properties, we investigate the conditional diagnosability of (n; k)-star graphs under the PMC model, and show that it is 1) n 2

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