论坛时间：2021年12月10日14:30-16:40
论坛形式：腾讯会议，ID 722 438 996
报告及报告人简介
报告1:区块链–零信任之上的共识
报告人：成秀珍 教授
报告人单位：山东大学
报告时间：2021年12月10日，14:30-15:30
报告人简介：
成秀珍教授现担任山东大学计算机科学与技术学院院长及山东省数链融合技术创新中心主任，是IEEE Fellow、国家高层次海外人才、国家重点研发计划首席科学家、山东省“泰山学者”海外特聘专家。成教授于1991年本科毕业于国防科技大学电子工程系，2002年博士毕业于美国明尼苏达大学双城分校计算机科学系。从2002到2020年在美国乔治华盛顿大学历任助理教授、终身副教授、终身教授。现主要研究方向为安全与隐私保护、区块链理论与应用、物联网与边缘计算等。曾担任（或正在担任）多家期刊编委及多个国际会议主席，是CCF C类国际学术会议WASA的创办者和国际期刊《High-Confidence Computing》的创办主编。
报告简介：
本报告主要回答两个问题：1、为什么说区块链的本质是零信任情况下实现多主体间成功协作的技术；2、拓展区块链应用面临哪些挑战。最后介绍一下我们在区块链方向上所做的一些工作。
报告2: Big Data Analytics for Intelligent Network Management
报告人：Prof. Geyong Min
报告人单位：英国埃克塞特大学
报告时间：2021年12月10日，15:30-16:30
报告人简介：
Professor Geyong Min is a Chair in High Performance Computing and Networking in the Department of Computer Science at the University of Exeter, UK. His research interests include Computer Networks, Cloud and Edge Computing, Mobile and Ubiquitous Computing, Systems Modelling and Performance Engineering. His recent research has been supported by European Horizon-2020, UK EPSRC, Royal Society, Royal Academy of Engineering, and industrial partners. He has published more than 200 research papers in leading international journals including IEEE/ACM Transactions on Networking, IEEE Journal on Selected Areas in Communications, IEEE Transactions on Computers, IEEE Transactions on Parallel and Distributed Systems, and IEEE Transactions on Wireless Communications, and at reputable international conferences, such as SIGCOMM-IMC, INFOCOM, and ICDCS. He is an Associated Editor of several international journals, e.g., IEEE Transactions on Computers, and IEEE Transactions on Cloud Computing. He served as the General Chair or Program Chair of a number of international conferences in the area of Information and Communications Technologies.
报告简介：
The past years have witnessed an explosive growth in the volume of network data driven by the popularization of smart mobile devices and pervasive content-rich multimedia applications, creating a critical issue of Internet traffic flooding. A pressing challenge is how to handle the ever-increasing network traffic and achieve smart network management. To address this challenge, our vision is to conduct efficient data analysis in order to dig valuable knowledge and actionable insights hidden in network big data for improving the design, operation, and management of future Internet. This talk will present innovative big data modelling and processing technologies, real-time data analysis tools, and a cost-effective distributed big data processing platform developed to support intelligent decision-making for system design, anomaly detection, resource management and optimization. This talk will offer the theoretical underpinning for efficient big data analytics and open up a new horizon of research and development by exploiting the key intelligence and insights hidden in content-rich big data for effective design and smart management of Cloud computing and networking systems.
