Keynote Speakers

Prof. Arumugam Nallanathan
IEEE Fellow
Queen Mary University of London, UK

Arumugam Nallanathan is Professor of Wireless Communications and Head of the Communication Systems Research (CSR) group in the School of Electronic Engineering and Computer Science at Queen Mary University of London since September 2017. He was with the Department of Informatics at King’s College London from December 2007 to August 2017, where he was Professor of Wireless Communications from April 2013 to August 2017 and a Visiting Professor from September 2017. He was an Assistant Professor in the Department of Electrical and Computer Engineering, National University of Singapore from August 2000 to December 2007.
His research interests include Artificial Intelligence for Wireless Systems, 5G and beyond Wireless Networks, Internet of Things (IoT) and Molecular Communications. He published nearly 500 technical papers (including more than 200 top IEEE journal papers) in scientific journals and international conferences. He is a co-recipient of the Best Paper Awards presented at the IEEE International Conference on Communications 2016 (ICC’2016), IEEE Global Communications Conference 2017 (GLOBECOM’2017) and IEEE Vehicular Technology Conference 2017 (VTC’2017). He is an Editor for IEEE Transactions on Communications and a Senior Editor for IEEE Wireless Communications Letters. He was an Editor for IEEE Transactions on Wireless Communications (2006-2011), IEEE Transactions on Vehicular Technology (2006-2017) and IEEE Signal Processing Letters. He served as the Chair for the Signal Processing and Communication Electronics Technical Committee of IEEE Communications Society and Technical Program Chair and member of Technical Program Committees in numerous IEEE conferences. He received the IEEE Communications Society SPCE outstanding service award 2012 and IEEE Communications Society RCC outstanding service award 2014. He has been selected as a Web of Science (ISI) Highly Cited Researcher in 2016. He is an IEEE Fellow and IEEE Distinguished Lecturer.

Speech Title: Machine Learning in Massive IoT Networks
Narrow Band-Internet of Things (NB-IoT) is an emerging cellular-based radio access technology, which offers a range of flexible configurations for different coverage enhancement (CE) groups to provide reliable uplink connections for massive IoT devices with diverse data traffic. To optimize the number of served IoT devices, the uplink resource configurations need to be adjusted in real-time according to the dynamic traffic, this brings the challenge of how to select the configurations at the Evolved Node B (eNB) in the multiple CE groups scenario with high-dimension and interdependency. Multi-agent reinforcement learning (RL) is a promising solution, where the RL agent (i.e., implemented at the eNB) automatically updates the uplink resource configuration by interacting with the environment (i.e., the communication procedures in NB-IoT). In this talk, Professor Nallanathan will explain how the machine learning techniques such as deep learning, artificial neural networks (ANN) can be used dynamically to tackle the numerous challenges in the massive Internet of Things (IoT).

Prof. Shugong Xu
IEEE Fellow
Shanghai University, China

Prof. Shugong Xu is a Professor at Shanghai University, an IEEE Fellow, head of the Shanghai Institute for Advanced Communication and Data Science (SICS). In his 20+ years career in research (over 15 years in industrial research labs), he had over 40 issued US/WO/CN patents and published more than 100 peer-reviewed research papers. His work was one of the major triggers to the research and standardization of IEEE 802.11S. He was awarded "National Innovation Leadership Talent" from China government in 2013, IEEE Fellow for "contributions to the improvement of wireless network efficiency" in 2015. Shugong also won 2017 Award for Advances in Communication from IEEE Communication Society. Shugong received his BS degree from Wuhan University, ME and PhD degrees from Huazhong University of Science and Technology (HUST). His current research interests includes 5G systems and Machine Learning.

Prof. Sergei Gorlatch
University of Muenster, Germany

Prof. Sergei Gorlatch is Full Professor of Computer Science at the University of Muenster (Germany) since 2003. Earlier he was Associate Professor at the Technical University of Berlin, Assistant Professor at the University of Passau, and Humboldt Research Fellow at the Technical University of Munich, all in Germany. Prof. Gorlatch has more than 200 peer-reviewed publications in renowned international books, journals and conferences. He was principal investigator in several international research and development projects in the field of software for parallel, distributed, Grid and Cloud systems and networking, funded by the European Community and by German national bodies.

Speech Title: Distributed Applications Based on Mobile Cloud and Software-Defined Networks
We consider an emerging class of challenging software applications called Real-Time Online Interactive Applications (ROIA). ROIA are networked applications connecting a potentially very high number of users who interact with the application and with each other in real time, i.e., a response to a user’s action happens virtually immediately. Typical representatives of ROIA are multiplayer online computer games, advanced simulation-based e-learning and serious gaming. All these applications are characterized by high performance and QoS requirements, such as: short response times to user inputs (about 0.1-1.5 s); frequent state updates (up to 100 Hz); large and frequently changing numbers of users in a single application instance (up to tens of thousands simultaneous users). This talk will address two challenging aspects of software for future Internet-based ROIA applications: a) using Mobile Cloud Computing for allowing high application performance when a ROIA application is accessed from multiple mobile devices, and b) managing dynamic QoS requirements of ROIA applications by employing the emerging technology of Software-Defined Networking (SDN).