By Ellen Tsaprailis Photos by Lindsay Ralph
Mengyao Wu is researching ways in which multi-access edge computing can better support connected intelligence for autonomous driving through his Ericsson Fellowship at Carleton University.
Cloud computing is applied in more and more solutions everyday and has provided the ability to host applications, web services or enterprise applications. However, the architecture of cloud computing is challenged when computing servers and high-volume data sources are geographically distant. When computation needs to be performed in real-time but the data cannot be transported in real-time, then this architecture fails. This is where edge computing comes in. Edge computing is a distributed computing framework that brings applications closer to data sources to improve response times.
Wu enjoys the connected intelligence aspect to autonomous driving and is hoping to figure out how best to implement edge computing.
“I look at advanced networking infrastructure and functionality to assist autonomous driving. Research, communication and computation are integrated,” says Wu. “Sometimes if the autonomous vehicle has limited computing resources but they want to do some object detection or complex calculation, they can send the task to the edge computing resources. Think of it as a small server attached to a base station.”
Wu explains that the autonomous vehicle itself has limited computing capability so it requires computation offloading so the computation task needs to be sent to another location with better computer resources which would involve edge computing. In addition to providing computation offloading, 5G-and-Beyond multi-access edge computing plays a vital role to support and revolutionize collective learning for autonomous vehicles.
“Just like we humans share knowledge with each other, autonomous vehicles can also do that with the help of advanced networking infrastructure,” says Wu. “When autonomous vehicles encounter new driving scenarios, they can collect data, extract information, and share their learning results to others. To co-ordinate such learning schemes, we need computing, caching and security as an integrated service operating close to autonomous vehicles. This is exactly the role of multi-access edge computing.”
Recently, Wu wrote a paper titled, “Intelligence Networking for Autonomous Driving in Beyond 5G Networks with Multi-access Edge Computing” which has been accepted for publication with journal IEEE Transactions on Vehicular Technology. The intelligence networking framework proposed in this paper supports collective learning for autonomous vehicles and adapting to environmental changes in near real-time.
Richard Yu is a cross-appointed Professor at Carleton’s School of Information Technology and the Department of Systems and Computer Engineering. He is also an academic supervisor of Wu’s research along with Systems and Computer Engineering Professor Peter Liu.
"With support from Ericsson, Mengyao is working on cutting-edge research related to 5G/6G cellular networks, edge computing and connected intelligence,” says Professor Yu. “We are very grateful for the great support from Ericsson."
Wu is one of six graduate students who are Ericsson Fellows at Carleton University—a unique, talent-building program born out of the Ericsson-Carleton University Partnership for Research and Leadership in Wireless Networks.
Instead of working as a teaching assistant during their graduate studies, Wu and the other fellows are being supported to focus on their pioneering wireless communications research and get input from both their academic supervisors and Ericsson professionals.
Wu completed his Bachelor of Engineering from Carleton and during his undergraduate program completed two co-op placements. The first one was at Irdeto Ottawa as a test automation developer for four months. He followed that up with a 14-month co-op placement at Ericsson Ottawa working as an indoor radio software developer.
In September of 2020, Wu began a Master of Applied Science as well as his Ericsson Fellowship. After a year of his master’s program, he took an accelerated pathway and applied for the PhD program in computer engineering in which he was accepted and is now pursuing.
Hoping to finish his PhD within the next three years, Wu’s future career goal is to continue conducting research.
“I want to do useful research and to achieve this goal I can try to become a university professor or I can hopefully work directly at Ericsson doing industrial research,” says Wu.
Ericsson FellowshipIn this prestigious fellowship program, Carleton graduate students conduct hands-on research alongside Ericsson experts in state-of-the-art facilities, ensuring students build skills that are in high demand in today's telecommunications industry.
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