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ICMCT 2021 Keynote Speakers

Yan Zhang, University of Oslo, Norway
张彦,挪威奥斯陆大学
欧洲科学院院士,挪威皇家科学院院士,挪威工程院院士,IEEE Fellow

 


中文简介:张彦现任挪威奥斯陆大学 ( U.S. NEWS世界百强名校,软科世界百强名校)信息工程学院教授。2005年毕业于新加坡南洋理工大学获电子电气工程博士学位,分别于北京航空航天大学和南京邮电大学获硕士和学士学位。近期主要研究方向为新一代6G无线通信网络和智能安全物联网(包括智能电网,车联网)。自2018年起,连续三年入选全球“高被引科学家”,并入选2020年Guide2Research计算机科学和电子学领域全球顶尖科学家千人榜单。任IEEE绿色通信与计算技术委员会主席,IEEE通信学会杰出讲师, IEEE车载技术学会杰出讲师。任CCF高级会员,CCF区块链专委会委员,并获评2019年CCF杰出演讲者。目前担任10个IEEE Transactions/Magazine期刊编委;及国内多个核心期刊编委。

Yan Zhang is a Full Professor at Department of Informatics, University of Oslo, Norway. He received a Ph.D. degree in School of Electrical & Electronics Engineering, Nanyang Technological University, Singapore. He received M.S. and B.S from Beihang University and Nanjing University of Post and Telecommunications, respectively. His current research interests include: 6G and Internet of Things (e.g., transport, smart grid). He received the prestigious award Clarivate Analytics(previously Thomson Reuters) "Highly Cited Researcher" since 2018.
He is IEEE Fellow and IET Fellow. He is an elected Fellow of Academia Europaea (MAE), an elected Fellow of Royal Norwegian Society of Sciences and Letters Academy (DKNVS) and an elected Fellow of Norwegian Academy of Technological Sciences (NTVA). He serves as the Chair of IEEE ComSoc TCGCC (Technical Committee on Green Communications & Computing). He is IEEE Communication Society Distinguished Lecturer and IEEE Vehicular Technology Society (VTS) Distinguished Speaker. He was IEEE VTS Distinguished Lecturer for two terms (2016-2018 and 2018-2020). He is a member of IEEE VTS Fellowship and Scholarship Committee. He is currently serving as an Area Editor/Senior Editor/Editor of 10 IEEE Transactions/Magazines, including IEEE Network Magazine; IEEE Communications Surveys & Tutorials; IEEE Transactions on Network Science and Engineering; IEEE Transactions on Industrial Informatics; IEEE Transactions on Vehicular Technology; IEEE Transactions on Green Communications and Networking; IEEE Internet of Things Journal; IEEE Systems Journal; IEEE Vehicular Technology Magazine and IEEE Blockchain Technical Briefs.

Topic: Digital Twin for 6G and IoT

 



Yonghui Li, ARC Future Fellow, IEEE Fellow
Professor. Dr., The University of Sydney, Australia

Yonghui Li is a Professor and Director of Wireless Engineering Laboratory, in School of Electrical and Information Engineering, the University of Sydney. He is the recipient of the prestigious Australian Research Council (ARC) Queen Elizabeth II Fellowship in 2008 and ARC Future Fellowship in 2012. His current research interests are in the area of wireless communications, Internet of Things, Wireless networks, 5G and wireless AI. He participated in $500million Australian national Smart Grid Smart City project, the world first large-scale demonstration project. He has published more than 300 papers in IEEE journals and conferences. Several of his journal papers have been included in ESI highly cited papers. According to google scholar, his research works have been cited more than 10000 times. He is now an editor for IEEE Transactions on Communications, and IEEE Transactions on Vehicular Technology. He also served as a guest editor for several special issues of IEEE journals, such as IEEE JSAC special issue on Millimeter Wave Communications, IEEE Communications Magazine on Wireless AI, IEEE IoT Journal, IEEE Transactions on Industrial Informatics, IEEE Access. He received several best paper awards from IEEE International Conference on Communications (ICC) 2014, IEEE PIMRC 2017 and IEEE Wireless Days Conferences (WD) 2014.

Title: 5G IoT Networks
Abstract:
Connected smart objects, platforms and environments have been identified as the next big technology development, enabling significant society changes and economic growth. The entire physical world will be connected to the Internet, referred to as Internet of Things (IoT). The intelligent IoT network for automatic interaction and processing between objects and environments will become an inherent part of areas such as electricity, transportation, industrial control, utilities management, healthcare, water resources management and mining. Wireless networks are one of the key enabling technologies of the IoT. They are likely to be universally used for last mile connectivity due to their flexibility, scalability and cost effectiveness. The attributes and traffic models of IoT networks are essentially different from those of conventional communication systems, which are designed to transmit voice, data and multimedia. IoT access networks face many unique challenges that cannot be addressed by existing network protocols; these include support for a truly massive number of devices, the transmission of huge volumes of data burst in large-scale networks over limited bandwidth, and the ability to accommodate diverse traffic patterns and quality of service (QoS) requirements. Some IoT applications have much stringent latency and reliability requirements which cannot be accommodated by existing wireless networks.  Addressing these challenges requires the development of new wireless access technologies, underlying network protocols, signal processing techniques and security protocols. In this talk, I will present the IoT network development, architecture, key challenges, requirements, potential solutions and recent research progress in this area, particularly in 5G.

 

 

Shangguang Wang,
Professor. Dr., Beijing University of Posts and Telecommunications, China

Shangguang Wang is a Professor at the School of Computing, Beijing University of Posts and Telecommunications, China. He received his Ph.D degreeat Beijing University of Posts and Telecommunications in 2011. He is a Vice-Director of the State Key Laboratory of Networking and Switching Technology. He has published more than 150 papers, and his research interests include service computing, mobile edge computing, cloud computing, and Space-air-ground Computing. He served as General Chairs or TPC Chairs of IEEE EDGE 2020, IEEE CLOUD 2020, IEEE SAGC 2020, IEEE EDGE 2018, and IEEE ICFCE 2017, etc., and Vice-Chair of IEEE Technical Committee on Services Computing (2015-2018). He is currently serving as Executive Vice-Chair of IEEE Technical Committee on Services Computing (2021-), and Vice-Chair of IEEE Technical Committee on Cloud Computing (2020-).

 

Fangming Liu,
Professor. Dr., Huazhong University of Science and Technology, China

刘方明,华中科技大学教授、博导,国家优秀青年科学基金获得者、国家高层次人才特殊支持计划(中组部“万人计划”)青年拔尖人才,入选爱思唯尔中国高被引学者。本科毕业于清华大学,博士毕业于香港科技大学,后作为加拿大多伦多大学访问学者、微软亚洲研究院“铸星计划”访问研究员。长期从事分布式系统与网络领域的相关研究(包括云计算与边缘计算、数据中心与绿色计算、5G与网络虚拟化等),主持国家重点研发计划课题、NSFC-DFG中德国际合作项目、国家自然科学基金、华为公司横向合作项目等,并参与承担了973计划青年科学家项目、863计划子课题、国家自然科学基金重点项目、重点国际合作项目等。一系列论文发表在ACM/IEEE ISCA、USENIX ATC、ACM/IFIP/USENIX Middleware、IEEE INFOCOM、ICNP、ICDCS等著名国际学术会议、以及IEEE百年汇刊Proceedings of the IEEE封面主题论文(ESI高被引)、TON、TPDS、TC、TMC、JSAC、CSUR、TCC、TBD、TSUSC、TOMPECS等IEEE/ACM Transactions,获批美国发明专利两项及中国发明专利十余项,获得IEEE/ACM IWQoS 2019、ACM e-Energy 2018和IEEE GLOBECOM 2011等多项国际学术会议最佳论文奖、2020年国家自然科学二等奖、2018年教育部自然科学一等奖。曾任国家自然科学基金委信息学部会评专家、科技部“创新人才推进计划”暨“万人计划”中青年科技创新领军人才和重点领域创新团队会评专家、香港研究资助局(RGC)项目外审专家、担任CCF A类国际学术会议WWW、ACM Multimedia、IEEE INFOCOM程序委员会委员,担任CCF互联网专委会委员和分布式计算与系统专委会委员。

Speech Title: Shaping the Cloud and Edge from a new QoS/QoE (Quality-Open-Smart-grEen) Perspective

Abstract: Cloud computing and cloud storage upon large-scale datacenters (DCs) and content delivery networks (CDNs), are becoming the fundamental paradigm of multiplexing and managing massive computing, storage, networking and big data resources as utility, which host a wide range of Internet-scale services and applications. Meanwhile, edge computing has recently emerged as a complementary paradigm to further optimize latencies, save bandwidth costs and preserve security/privacy requirements. In this talk, we envision a four-dimensional development trend of both cloud and edge in terms of Quality-Open-Smart-grEen (QoS/QoE), by not only exploring new design space and open source deployment of emerging cloud and edge eco-systems at the service-level spectrum (such as multiple inter-clouds and hybrid cloud-edge interplays), but also identifying challenges and opportunities of underlying DC resource management at the infrastructure-level spectrum (such as SDN/NFV-enabled DC performance guarantee and ML/data-driven energy efficiency optimization). Concrete case studies and inspiring research results will be illustrated to bridge theory and practice, so as to foster comprehensive brainstorming and cross-disciplinary collaboration for shaping the future cloud and edge.

 

 

 

 

 

 

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