Intelligent 5G/B5G Service Function Chain Provisioning

This project aims to solve a primary problem of 5G/B5G Networks, namely the Service Function Chain (SFC)
provisioning problem. This project will improve the solutions for this problem in two aspects. First, the SFC architectures considered in this project are futuristic/generalized ones that do not appear in existing systems. These architectures reduce the processing time of services by concurrently performing tasks at different locations. These sophisticated systems represent a complicated SFC provisioning problem that has received very little attention in the literature. Second, this project will improve existing provisioning solutions by robust traffic prediction frameworks. Most of the existing traffic prediction frameworks consider only one location at a time and rely on historical data strongly. Data traffic patterns at different locations correlate mutually. And historical data is not usually available because of stringent privacy agreements. This project will apply the latest Artificial Intelligence and Machine Learning techniques, especially online learning, to design robust solutions and evaluations. For Ciena – a leading organization in the networking service industry, this research project adheres to Ciena with innovative technologies of 5G/B5G Networks. Ciena may get prototypes from this project that lead to products in the future. The research outcomes can also confirm the effectiveness

Faculty Supervisor:

Brigitte Jaumard;Abdelhak Bentaleb

Student:

Partner:

Ciena Corporation (Ottawa, ON)

Discipline:

Computer science

Sector:

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

University:

Concordia University

Program: