Optimizing Service Provisioning in 5G Networks through Robust Heuristic

Description

A dense deployment of small cells is one of the key characteristics envisioned for future 5G mobile networks in order to provide the required capacity increase where needed. In this context, it becomes very important to develop strategies to turn on and off the small cells according to the users’ needs, so to reduce costs and CO2 emissions. A fast robust heuristic has been recently developed in Optaplanner that considers a snapshot of the 5G network and provides a jointly optimized solution for the association of mobile users and the routing in the backhaul mesh.

This Ph.D. focuses on providing a new metaheuristic model that improves the previously available heuristic solutions. The metaheuristic approach will be general enough to fit different scenarios. A self-configuration approach is considered mandatory, so that machine learning techniques will be used to tune input parameters properly.   

Period

Start date: --
End date: --
Status: Open

Funding

No funding is provided for this project.

Participants

Supervisor: Enrica Zola (GRXCA)

Student: To be assigned.

Further information

No additional information is provided.