Conditional Diagnosability of (n k)-Star Networks Under the PMC Model

Abstract

Processor fault diagnosis has played an important role in measuring the reliability of a multiprocessor system; the diagnosability of many well-known multiprocessor systems has been widely investigated The conditional diagnosability is a metric that can give the maximum number of conditional faulty set that the system is guaranteed to identify It is impossible that all adjacent vertices of one vertex are faulty simultaneously This thesis shows that the conditional diagnosability of (n k)-star graphs for (n ? 4 k = 1) and (n ? 5 2 ? k ? n - 3) and (n ? 5 k = n - 2) under the PMC model

Date of Award	2016 Aug 4
Original language	English
Supervisor	Sun-Yuan Hsieh (Supervisor)