IoT Thrust Seminar


Towards efficient resource utilization in wireless networks for smart cities

10:15am - 11:15am
Zoom Meeting ID: 939 2221 8331, Passcode: 499138

Smart cities are constantly evolving ecosystems, offering individuals a safer, more intelligent, sustainable way of living. The success of smart cities relies on emerging technologies, such as Internet of things, artificial intelligence, high-definition video streaming, and mixed reality. Despite significant progress in these emerging technologies, the recent wireless networking infrastructure may be unable to support these technologies due to their large networking, computation, and storage requirements. In this talk, I will present frameworks and methodologies for empowering the wireless networking infrastructure to effectively support smart cities. In particular, we first focus on mobile edge computing systems and propose a deep reinforcement learning-based algorithm, which can effectively reduce the task processing latency. We also explore the potential benefits of joint resource sharing among mobile devices. Based on such resource sharing models, I will discuss how stochastic control, online convex optimization, and game theory can be employed for improving resource efficiency. Furthermore, specific applications (e.g., high-definition video streaming, virtual reality) are considered in our work to improve the service provisioning in smart cities under limited network resources. I will further provide visions of how machine learning techniques and wireless networking infrastructure can coordinate to make smart cities a reality.

10:15am - 11:15am
Zoom Meeting ID: 939 2221 8331, Passcode: 499138
Event Format
Speakers / Performers:
Dr. Ming Tang
The University of British Columbia, Vancouver, Canada

Dr. Ming Tang is a postdoctoral fellow in the Department of Electrical and Computer Engineering at The University of British Columbia, Vancouver, Canada. She received her Ph.D. degree in the Department of Information Engineering at The Chinese University of Hong Kong in September 2018. During her Ph.D. study, she was awarded the Hong Kong Ph.D. Fellowship. From September 2017 to March 2018, she was a visiting student in the Department of Management Science and Engineering at Stanford University. Her research focuses on mobile edge computing systems, Internet of things, federated learning, crowdsourced intelligence, and mobile video streaming.

Recommended For
Faculty and staff
PG students
Department of Electronic & Computer Engineering
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