报告题目【Two-step local diagnosis algorithm under PMC model】

时间：2018年8月3日(星期五)下午 16:30

地点：仓山校区成功楼603报告厅

主讲：苏州大学，林政宽教授

主办：数学与信息学院、福建省网络安全与密码技术重点实验室

参加对象：数信学院、网络安全与密码技术重点实验室相关教师与研究生

报告摘要：Fault diagnosis is important to the design and maintenance of large multiprocessor systems.?An efficient diagnosis is very important for a multiprocessor system. The ability of identifying all the faulty devices in a multiprocessor system is known as diagnosability. The PMC model is the tested-based diagnosis with a processor performing the diagnosis by testing on the neighboring processors via the links between them.?If states of all system units are identified in a single step of the syndrome-decoding process, the system is referred to as one-step diagnosable system.?Hsu and Tan?(A local diagnosability measure for multiprocessor systems, IEEE TPDS,?18?(2007) 598-607)?proposed the concept of local diagnosability to identify the diagnosability of a individual multiprocessor. For a processor?v?in a system, the only requirement is to determine whether or not?v?is faulty. In this talk, we will propose a two-step local diagnosis algorithm to determine the states of a processor, which allow repairing a faulty neighbor of it. For a?t-diagnosable system, if there exist more than?3t-1?faulty processors, our algorithm will precise?determine the states of a processor.

报告人简介：Cheng-Kuan Lin received his B.S. degrees in Applied Mathematics from the Chinese Culture University in 2000; and received his M.S. degrees in Mathematic from the National Central University in 2002. He obtained his Ph. D. in Computer Science from the National Chiao Tung University in 2011. He served as a Member of Mathematical Reviews in the American Mathematical Society (2007.12 -present). He served as a Member of Technical?Program Committee Members for many internal conferences. He is a distinguished associate professor at the School of Computer Science and Technology at Soochow University. His research interests includes graph theory, design and analysis of algorithms, discrete mathematics, wireless sensor networks, mobile computing, wireless communication, wireless applications, and parallel and distributed computing.