AI-Powered Traffic Flow Characterization, Monitoring and Prediction
Investigators
Shafiq , Omair
- Assistant Professor, IRM Coordinator, School of Information Technology
- OmairShafiq@cunet.carleton.ca
- 6135202600 ext 6038
Team
- Nader Joojili
- Alexis Amezaga Hechavarria
Ericsson partners
Research project
In the era of 5G and the on-going COVID-19 pandemic, users and businesses have been relying on internet connectivity more than ever before. It is critical for modern network services to be well-planned, organized and monitored by system administrators and network service providers to ensure the highest possible availability, reliability, efficiency, and cost-effectiveness. Network traffic characterization and pattern prediction in-advance can further empower network service providers to plan, design, and optimize networks, and eventually to ensure high quality and cost-effective network services to their users.
The overall objective of this project is to design and develop novel and innovative solutions to monitor network traffic, detect existing and discover new patterns, and predict traffic patterns in advance.
The research team will utilize the latest state of the art machine learning and deep learning techniques and will carry out an extensive evaluation of the solutions and compare their functionality and performance with existing solutions.