Date: 23 Mar 2021
Time: 07:00 PM to 08:00 PM
Speaker(s): Haixia Peng
Organizer(s): IEEE Toronto VT Chapter
Contact: Lian Zhao
Abstract: Benefiting from advances in the automobile industry and wireless communication technologies, the vehicular network has been emerged as a key enabler of intelligent transportation services. However, with more and more services and applications, mobile data traffic generated by vehicles has been increasing and the issue of the overloaded computing task has been getting worse. Because of the limitation of spectrum resources and vehicles’ onboard computing/caching resources, it is challenging to promote vehicular networking technologies to support the emerged services and applications, especially those requiring sensitive delay and diverse resources. To effectively address the above challenges, two potential technologies, multi-access edge computing (MEC) and unmanned aerial vehicle (UAV), can be exploited in vehicular networks. In this presentation, I will introduce how to adopt optimization and AI technologies for efficient resource slicing, and therefore supporting various applications with satisfied quality of service (QoS) requirements in MEC- and/or UAV-assisted vehicular networks. For a relatively simple vehicular network scenario with only terrestrial MEC servers, a model-based method is applied for dynamic spectrum management, including spectrum slicing, spectrum allocating, and transmit power controlling. For a vehicular network supported by both terrestrial and aerial MEC servers, an AI-based method is applied to effectively manage the spectrum, computing, and caching resources while satisfying the QoS requirements of different applications.
Haixia Peng received her M.S. and Ph.D. degrees in Electronics and Communication Engineering and Computer Science from Northeastern University, Shenyang, China, in 2013 and 2017, respectively. She is currently a Ph.D. student in the Department of Electrical and Computer Engineering at the University of Waterloo, Canada. Her current research focuses on Internet of vehicles, resource management, multi-access edge computing, and reinforcement learning. She has authored or co-authored more than 30 technical papers dealing with network issues. 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. more than 20 prestigious journals, and as a TPC member in IEEE ICC, Globecom, VTC, etc. conferences.