AI 5G network management optimization
Prof. SCHEMBRA Giovanni
Orhestration and resource allocation will play a crucial role in management of the future 5G systems. In this context application of Artificial intelligence (AI) techniques will be challenging in optimizing performance and reducing energy consumption to enable new services, today unfeasible. Objective of the work is to define machine learning technique in a softwarized network environment realized with Linux Dockers and Containers managed with Kubernetes.