报 告 人: 张乃文博士 成功大学
报告题目：Conditional diagnosability of Cayley graphs generated by transpositions trees under the PMC model
时 间：
地 点：仓山校区成功楼603报告厅
主 办：数学与计算机科学学院，福建省网络安全与密码技术重点实验室
参加对象：数计学院和重点实验室相关专业的教师和研究生
报告摘要: Processor fault diagnosis has played an essential role in measuring the reliability of a multiprocessor system; the diagnosability of many well-known multiprocessor systems has been widely investigated. Conditional diagnosability is a novel measure of 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 Cayley graphs are exhibited. Based on these properties, we investigate the conditional diagnosability of Cayley graphs generated by transposition trees under the PMC model, and show that it is 4n-11 for n>= 4, except for the n-dimensional star graph, for which it has been shown to be 8n-21 for n>= 5 (refer to [Chang and Hsieh 2014]).
专家简介：2001年6月毕业于台湾大学数学系，2005年6月, 2010年6月相继毕业于台湾成功大学计算机专业，获硕士和博士学位，2011年6月--2013年7月成功大学博士后研究员，2014年至今成功大学资讯工程系助理研究员。张乃文博士主要从事大规模计算机系统的故障诊断与检测以及网络系统的容错性能分析，其科研成果相继发表于IEEE Transactions on Computers、IEEE Transactions on on Parallel and Distributed Systems、IEEE Transactions on Reliability、IEEE Transactions on Dependable and Secure Computing、ACM Transactions on Design Automation of Electronic Systems。