AI powered Traffic Flow Characterization, Monitoring and Prediction

Users and businesses have been relying on internet connectivity more than ever before since the COVID-19 pandemic. 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 Ericsson help system administrators, network service providers to plan, design, and optimize networks, and eventually to ensure high quality and cost-effective network services to users. This project aims to design and develop novel and innovative solutions to monitor network traffic, detect existing and discover new patterns, and predict traffic patterns in advance.

Faculty Supervisor:

M. Omair Shafiq

Student:

Partner:

Ericsson Canada Inc (Quebec);Ericsson Canada Inc (Ottawa, ON)

Discipline:

Computer science

Sector:

Information and cultural industries; Manufacturing; Professional, scientific and technical services

University:

Carleton University

Program: