演讲者：何晓冬博士，京东 AI 研究院常务副院长
题目：When IoT meets Big Data
In the past decade, applications of Internet of Things (IoT) such as Smart Home, Smart Cities, Smart Healthcare etc. have been deployed where the devices in our surroundings are interconnected to provide better services and comfort to humans. More recently, we witness the emerging applications in industrial internet, supply chains and other areas where the scale of the systems, the number of devices and data being generated continuously increases. As the IoT continues to develop, further potential can be realized by a combination with related technology approaches including Big Data Computing. The intersection of IoT and Big Data is a fascinating area of innovation with tremendous scope for business impact. In this talk, I will describe the evolution of IoT from instrumentation and interconnection to intelligence driven by big data analytics. When IoT meets big data, we see the direction towards smart IoT, which will facilitate and empower advanced applications. I will focus on the current challenges and future development of smart IoT leveraging big data analytics
Dr. Cao is currently a Chair Professor of Department of Computing at The Hong Kong Polytechnic University, Hong Kong. He is also the director of the Internet and Mobile Computing Lab in the department and the director of University’s Research Facility in Big Data Analytics. His research interests include parallel and distributed computing, wireless sensing and networks, pervasive and mobile computing, and big data and cloud computing. He has co- authored 5 books, co-edited 9 books, and published over 600 papers in major international journals and conference proceedings. He received Best Paper Awards from conferences including IEEE DSAA 2017, IEEE SMARTCOMP 2016, IEEE ISPA 2013, IEEE WCNC 2011,etc. Dr. Cao served the Chair of the Technical Committee on Distributed Processing of IEEE Computer Society from 2012 to 2014, a member of IEEE Fellows Evaluation Committee of the Computer Society and the Reliability Society, a member of IEEE Computer Society Education Awards Selection Committee, a member of IEEE Communications Society Awards Committee, and a member of Steering Committee of IEEE Transactions on Mobile Computing. He has also served as chairs and members of organizing and technical committees of many international conferences, and as associate editor and member of the editorial boards of many international journals. Dr. Cao is a fellow of IEEE and ACM distinguished member. In 2017, he received the Overseas Outstanding Contribution Award from China Computer Federation.
题目：Mobility-Enhanced Edge in Telligence for Ultra-reliable and Low-Latency Communications (MEET-U)
As the Internet of Things (IoT) and 5G mobile communications technologies develops, a hyper-connected society that makes everything in the planet connected is becoming a reality. This will necessitate the future mobile networks to more flexibly and intelligently adapt to a wide range of services. Among them, the most critical and challenging ones are the so-called mission-critical applications such as industrial Internet, networked robotics, VR/AR/MR, and connected vehicles, which require ultra-reliable and low-latency communications (URLLC). To realize that, the future mobile networks need to be fueled with additional resources (not only spectrum and energy resources, but also compute and cache resources) and enhanced intelligence in a distributed manner so that the networks can be smart enough. As a result, big data analytics, mobile edge computing/caching (MEC) and artificial intelligence (AI) will play key roles.
Meanwhile, mobility has been considering as a major obstacle to mobile communications because it may cause fading, shadowing, near-far effect, handover, roaming, etc. However, as the electric vehicles and autonomous cars are getting more and more powerful with rich capabilities of sensing, communicating, computing, caching, and powering, they can be used as movable edge servers not only to provide task-offloading services opportunistically but also to disseminate the edge intelligence to the whole network while moving. In this regard, mobility is in fact exploited to enhance the network intelligence so that the URLLC services can be realized by making the critical applications meet with the movable intelligent servers opportunistically. The key questions then include (but not limit to): 1) how to collect and process the big data in a distributed manner and generate the edge intelligence locally? 2) how to disseminate the distributed intelligence across the whole network effectively? 3) how to find and assign the best opportunities to the moving users? 4) how to efficiently provide reliability and latency guarantees to mission-critical applications?
This talk will explore advanced artificial intelligence (AI) techniques for autonomous and smart decision-makings in future wireless networks. In particular, we will combine expertise on mobile communications and AI to leverage recent advances, such as in the field of deep learning, to develop traffic and network condition prediction methods that can be used for smart task-offloading and content-caching and optimized resource allocation. We are particularly interested in the development of autonomously evolving models of network sharing that aggregates resources across technologies, different operators, and service requirements.
Zhisheng Niu graduated from Beijing Jiaotong University, China, in 1985, and got his M.E. and D.E. degrees from Toyohashi University of Technology, Japan, in 1989 and 1992, respectively. During 1992-94, he worked for Fujitsu Laboratories Ltd., Japan, and in 1994 joined with Tsinghua University, Beijing, China, where he is now a professor at the Department of Electronic Engineering. His major research interests include queueing theory, traffic engineering, mobile Internet, radio resource management of wireless networks, and green communication and networks.
Dr. Niu has served as Chair of Emerging Technologies Committee (2014-15), Director for Conference Publications (2010-11), and Director for Asia-Pacific Board (2008-09) in IEEE Communication Society, and currently serving as Director for Online Contents (2018-19) and Area Editor of IEEE Trans. Green Commun. & Networks. He received the Outstanding Young Researcher Award from Natural Science Foundation of China in 2009 and the Best Paper Award from IEEE Communication Society Asia-Pacific Board in 2013. He was also selected as a distinguished lecturer of IEEE Communication Society (2012-15) as well as IEEE Vehicular Technologies Society (2014-18). He is a fellow of both IEEE and IEICE.