报告题目: Code Constructions and Fundamental Limits for Networked Computer Systems
报告人：Chao Tian, Texas A&M University
时间：7月19日，下午2：00
地点：伟德BETVLCTOR1946青岛校区信息学院N5楼4楼会议室
报告人简介：
Dr. Chao Tian received the B.E. degree in Electronic Engineering from Tsinghua University, Beijing, China, in 2000 and the M.S. and Ph. D. degrees in Electrical and Computer Engineering from Cornell University, Ithaca, NY in 2003 and 2005, respectively. Dr. Tian was a postdoctoral researcher at Ecole Polytechnique Federale de Lausanne (EPFL) from 2005 to 2007, a member of technical staff--research at AT&T Labs--Research in New Jersey from 2007 to 2014, and an Associate Professor in the Department of Electrical Engineering and Computer Science at the University of Tennessee Knoxville from 2014 to 2017. He joined the Department of Electrical and Computer Engineering at Texas A&M University as an Associate Professor in 2017. Dr. Tian received the Liu Memorial Award at Cornell University in 2004, AT&T Key Contributor Award in 2010, 2011 and 2013, and 2014 IEEE ComSoc DSTC Data Storage Best Paper Award. He was an Associate Editor for the IEEE Signal Processing Letters from 2012 to 2014, and is currently an Editor for the IEEE Transactions on Communications.
报告摘要：
Many networked computer systems have multiple components which need to communicate with each other to satisfy certain functional requirements. As computation power becomes more abundant in many modern computer systems, they should in fact be viewed as communication-resource- constrained systems, and thus codes should be designed under such constraints. In this talk, I will provide an overview and new results on four such systems, namely distributed data storage systems, multiuser caching systems, private information retrieval systems, and data structures to retrieve partial sums. Two common themes of interest are to design efficient codes and to identify the fundamental limits for such systems. For the former task, we discuss either algebraic codes or Shannon-theoretic coding schemes, and for the latter, we discuss a novel semi-automated approach based on linear programing, which facilitates the identification of such fundamental limit.