Lian Zhao

In the 5G era, wireless networks are anticipated to provide connectivity for massive mobile devices and to enable a variety of innovative applications, which generate enormous computing service demands with diverse and stringent Quality of Service requirements. To support the emerging computing service demands, Mobile Edge Computing (MEC), as a cutting-edge technology in 5G, utilizes computing resources on the network edge to provide computing services for mobile devices within a radio access network. In this talk, we will investigate computing resource management for MEC to satisfy diverse computing requirements in wireless networks. We will introduce three computation offloading and task scheduling schemes tailored for supporting representative use cases and network scenarios in 5G, including autonomous driving, Unmanned Aerial Vehicle (UAV) assisted networks, and highly dense vehicular networks. Machine learning algorithms are applied to facilitate low-latency and reliable computing services in complex and dynamic network environments. Speaker(s): Mushu Li Biography: Dr. Mushu Li received the Ph.D. degree from the University of Waterloo, ON, Canada, in 2021, and the M.A.Sc. degree from Ryerson University, Toronto, ON, Canada, in 2017. She is currently a Postdoctoral Fellow with the Department of Electrical and Computer Engineering, University of Waterloo.  Dr. Li was a recipient of the NSERC Canada Graduate Scholarship (2018-2021) and Ontario Graduate Scholarship in 2015 and 2016, respectively. Her research interests include Internet of vehicles, resource management, multi-access edge computing, and reinforcement learning. She has authored/co-authored over 20 technical papers. She serves/served as a reviewer for IEEE Journals on Selected Areas in Communications (JSAC), IEEE Transactions on Communications, IEEE Transactions on Vehicular Technologies, etc. Virtual: https://events.vtools.ieee.org/m/305769

The transition to electric vehicles (EVs) is gaining momentum around the world and the major drivers for this acceleration are the rising awareness by the public for maintaining a clean environment, reducing pollutant emissions, breaking dependencies on oil, as well as tapping into cleaner sources of energies. EVs acceptance however is hindered by several challenges; among them is their shorter driving range, slower charging rates, and the ubiquitous availability of charging locations, collectively contributing to higher anxieties for EVs drivers. To mitigate this anxiety, a naïve approach is to expand the charging network, while an unplanned expansion may challenge the generation, transmission and distribution sector of the grid along with being a potential cyber-physical attack platform. As a consequence, to attain a graceful EV penetration for curtailing GHG emission, along with the socioeconomic initiatives, an extensive research is required, especially to mitigate the range anxiety and ameliorate the load congestion on the grid. Fortunately, the IoT enabled charging ecosystem (i.e., EVs, charging stations, the grid etc.) enables smart and informed charging schemes to exploit the benefit of different distributed energy sources (e.g., renewable energy based standalone chargers, vehicle to grid or vehicle to vehicle energy transfer technology, etc.) to minimize the load burden of the grid. But, on the other hand, this IoT enabled charging ecosystem unveils a new cyber-physical attack surface and hence, new challenges also need to be addressed to make this charging ecosystem secure as well. Virtual: https://events.vtools.ieee.org/m/309875 Speaker: Dr. Mohammad Ekramul Kabir Biography: Dr. Mohammad Ekramul Kabir is currently working as a Horizon postdoctoral research fellow in CIISE at Concordia University, Montreal, Canada. He obtained his PhD on Information and Systems Engineering from Concordia University in May 2021. He has received the B.Sc. and M.S. degree in Applied Physics, Electronics and Communication engineering from University of Dhaka, Bangladesh. His research interests include green, smart, and secure charging of electric vehicle, cloud/edge computing security and applications of artificial intelligence. He is a coauthor of a number of peer-reviewed journal and conference papers. He also serves/served as a reviewer for IEEE Transactions on Transportation Electrification, IEEE Transactions on Vehicular Technology, IEEE Transactions on Mobile Computing, IEEE Transactions on Network and Service Management, IEEE Intelligent Transportation Systems Magazine, IEEE PES General Meeting, etc.

After two-years’ online events, IEEE Vehicular Technology Chapter of IEEE Toronto Section, is pleased to announce our first in-person Distinguished Lecturer (DL) Series Talks on June 23, 2022, for a theme as Connecting People/Things/Vehicles. This in-person series of talks will be a great opportunity to meet and chat and exchange with our International and National visitors, colleagues, and Chapter members in Toronto area. Details of the events are given below. All are welcome! Speaker(s): Dr. Duist Niyato, Dr. Jelena Mišić, Dr. Ping Wang, Dr. Hina Tabassum, Dr. Jie Gao Register: https://events.vtools.ieee.org/m/315859 Biographies: Dr. Ping Wang is an Associate Professor at the Department of Electrical Engineering and Computer Science, York University, and a Tier 2 York Research Chair. Prior to that, she worked with Nanyang Technological University, Singapore, from 2008 to 2018. Her research interests are mainly in the area of wireless communication networks, cloud computing and Internet of Things with the recent focus on integrating Artificial Intelligence (AI) techniques into communications networks. She has published more than 250 papers/conference proceedings papers. Her scholarly works have been widely disseminated through top-ranked IEEE journals/conferences and received the Best Paper Awards from IEEE Wireless Communications and Networking Conference (WCNC) in 2022, 2020 and 2012, from IEEE Communication Society: Green Communications & Computing Technical Committee in 2018, and from IEEE International Conference on Communications (ICC) in 2007. Her work received 21,000+ citations with H-index 70 (Google Scholar). She is an IEEE Fellow and a Distinguished Lecturer of the IEEE Vehicular Technology Society. Hina Tabassum is an Assistant Professor at the Lassonde School of Engineering, York University, Canada. Prior to that, she was a PDF at the Department of ECE, University of Manitoba, Canada. She received her PhD degree from King Abdullah University of Science and Technology (KAUST) in 2013. She is a Senior member of IEEE and a P.ENG in the province of Ontario. She has published over 70 technical articles in well-reputed IEEE journals and conferences. She is the founding chair of a special interest group on THz communications in IEEE ComSoc: Radio Communications Committee (RCC). She has been recognized as an Exemplary Editor by IEEE Communications Letters, 2020, and an Exemplary Reviewer (Top 2% of all reviewers) by IEEE Transactions on Communications in 2015-2017, 2019, and 2020. Currently, she is serving as an Associate Editor in IEEE Communications Letters, IEEE Transactions on Green Communications, IEEE Communications Surveys and Tutorials, and IEEE Open Journal of Communications Society. Her research interests include stochastic modeling, analysis, and optimization of energy efficient multi-band 5G/6G wireless networks jointly operating on sub-6GHz, millimeter, and Terahertz frequencies with applications to vehicular, aerial, and satellite networks. Agenda: Program Chair 1:30-1:33 Dr. Lian Zhao, Opening and welcome 1:33-2:15 Dr. Duist Niyato, “Metaverse virtual service management: game theoretic approaches” Dr. Khalid Hafeez 2:15-3:00 Dr. Jelena Mišić, “Blockchain in IoT based on practical Byzantine fault tolerance” Dr. Khalid Hafeez 3:00-3:15 Break 3:15-3:45 Dr. Ping Wang, “Towards Fast-Convergent Federated Learning with non-IID data” Dr. Jie Gao 3:45-4:15 Dr. Hina Tabassum, “Mobility-Aware Performance Optimization for Next Generation Vehicular Networks” Dr. Jie Gao 4:15-4:30 Break 4:30-5:00 Dr. Lian Zhao, “Computing offloading and task scheduling at network edge” Dr. Ajmery Sultana 5:00-5:30 Dr. Jie Gao, “Network Planning: from Slicing to Digital Twin”  Dr. Ajmery Sultana 5:40-5:33 Dr. Lian Zhao, Closing remark