Automating Configuration and Performance Management of Data Centers - Year two

Data centers (DCs) in network softwarization and 5G eras are significantly different from those operated nowadays by public cloud providers. They are massively distributed, closer to end-users, heterogeneous (e.g., multi-access edge, central office as a data center, etc.) and rely on much more complex technologies (e.g., Network Functions Virtualization [NFV] and Software-Defined Networking [SDN]). This makes their Operation and Management (O&M) much more challenging. Much more intelligence is required for automating the various tasks.

Just-In-Time Scaling of Cloud Based Video Games using Machine Learning

Ubisoft’s cloud-based video game ecosystems experience the workload up to 5+ millions players in a typical week. Workloads on game servers are of different scales, ranging from tens of clients per game server to thousands of clients for traditional workloads. To guarantee game player user experience, a pool of servers is launched to react to demands but servers are idles in most of the time. Scaling down servers is even more complex because of the persistent connections to maintain the states and records of players and games.

Fostering Indigenous Small-scale fisheries for Health, Economy and food Security in Cree communities of northern Quebec (FISHES)

Northern fisheries are facing major changes and reducing the negative impacts is crucial for communities tied to the fisheries for their food security and culture. The identification of regions important for subsistence, commercial and recreational harvesting and whether they comprise genetically distinct groups of populations is a key requirement for adaptive co?management of harvest. Our team is comprised of researchers and Indigenous collaborators that combine the expertise for implementing knowledge at the interface between genomics and fisheries management.

Detection and Prediction of Network Vulnerabilities with Machine Learning Models and Algorithms

The project investigates the development of artificial intelligence models and algorithms to analyze telecommunication networks, looking for signs that indicate the presence, or imminent arrival, of faults and outages on the network.
The project will use as its main input data (network topology and network health metrics) collected by EXFO in real-time and accumulated over extensive periods of time.

Improving the Reliability of AI Systems from a Software Engineering Perspective

Artificial Intelligence techniques have been widely applied to solve real-world challenges, from autonomous driving cars, to detecting diseases. With the popularity of 5G wireless network, more and more AI systems are being developed to provide convenient services to everyone. It is important to ensure the reliability and quality of AI systems from every phase in software development cycle, i.e., development, integration, deployment and monitoring. In this collaboration with Ericsson GAIA, we will propose techniques to systematically improve the quality and reliability of AI systems.

From humanitarian crises to pandemics: technology to the rescue

Who could have foreseen that humanitarian activities during the 2010 earthquake in Haiti would, 10 years later, guide the way for researchers, entrepreneurs and Mitacs interns during the COVID-19 crisis?

During his deployment at a Red Cross field hospital after the earthquake, Dr. Abdo Shabah saw the potential for greater use of technology in emergency health interventions.

What do researchers do when stuck abroad? Work on a COVID-19 vaccine

When Gurudeeban Selvaraj and Satyavani Kaliamurthi came to Canada in 2019, they had no idea they would be creating both a preventative vaccine and a curing drug to address the millennium’s biggest pandemic.

Québec__Concordia University

No additional funding contribution is required from the academic supervisor or university.
Fellowships will be awarded competitively.

Adaptive Slicing for Intelligent Network Automation

The forthcoming 5G networks will be much more complex than their predecessors. They are on the verge of a generational transformation driven by the coverage, connectivity, availability, speed and latency demands of 5G. 5G networks will use network slicing to open up the network “as a service” to various third parties and their diversified applications, e.g., from autonomous vehicle control to massive machine-type communication for IoT devices.

Multivariable PID Controller for Search and Rescue UAV Operations Based on Static Output Feedback

The research proposed in this document will build upon and extend the previously funded CRIAQ (AUT-1701) and MITACS (IT12130) projects on the development of a UAV platform for search and rescue activities in the ski facilities of Domain Saint Bernard in Mont Tremblant in collaboration with SII Canada. The goal of this research is to develop a synthesis methodology for a multivariable PID flight controller to steer a rescuing UAV to a person in danger using output feedback.