A PhD position is available in the team of Pr. Diala Naboulsi at the École de Technologie Supérieure (ÉTS), Montréal, Canada in September 2020.
Context: With the massive integration of connected devices, future mobile networks will need to accommodate both human-type and machine-type communications. In addition, the proliferation of new applications and services is imposing very heterogeneous and diverse requirements for future mobile networks to satisfy, in terms of latency, throughput and reliability. Network slicing has recently emerged as a key concept that allows supporting the wide variety of new services. Using virtualization technologies, network slicing allows building isolated logical networks, on a per-service basis, on top of a single physical network. Different architectures were proposed at this level, encompassing the Core Network (CN) and the Radio Access Network (RAN). These architectures employ Network Function Virtualization (NFV) and Software-Defined Network (SDN) technologies, providing a significant degree of flexibility in network management.
In this context, ensuring an efficient utilization of resources, while meeting end-to-end slices requirements is far from being an easy task. Human-type communication traffic and machine-type communication traffic are characterized by a high level of dynamicity that needs to be properly captured in designed solutions. Moreover, the presence of multiple-Radio Access Technologies (RATs), together with the high-density deployments in the future RANs impose additional challenges at this level. Finally, accounting simultaneously for the CN and RAN resources that differ in nature is not a straightforward job. Most of the existing network slicing resource allocation studies either focus on CN or RAN. Accordingly, this research project addresses the following question: How to enable an efficient joint utilization of CN and RAN resources for network slicing?
The objective of the project is to derive resource allocation solutions for network slicing that account for i) mobile traffic dynamics, ii) heterogeneous slices requirements and iii) the presence of multiple RATs with high-density deployments. Dynamic joint CN and RAN adaptive slicing algorithms will be proposed to fulfill an end-to-end set of requirements in terms of latency, throughput and reliability.
Collaborations and Scholarship
The work will be conducted in collaboration with Pr. Razvan Stanica, INSA Lyon, France. A scholarship is granted for four years.
Qualifications and Requirements
The position requires:
- A master’s degree in Electrical or Computer Engineering, Computer Science, or a related discipline
- Excellent writing, communication and presentation skills in English
- Solid knowledge in: i) wireless and mobile networks, ii) optimization and reinforcement learning
- Strong coding skills in Python, Java, C or C++
How to Apply:
Interested applicants must send the following documents, in a single PDF file, to email@example.com
- Detailed CV
- M.Sc. & B.Sc. transcripts
- List of all publications, if any
- Motivation letter
- A letter of recommendation is a plus
Applications will be reviewed until the position is filled.