Artificial Intelligence in virtualized networks: a journey

This paper provides an overview of the research activities in the area of Artificial Intelligence applied to Network Function Virtualization (NFV), carried out by Vodafone, jointly with Scuola Superiore Sant’Anna of Pisa. Artificial Intelligence techniques have been used on system-level data gathered from Virtual Machines (VMs) composing a multitude of Virtualized Network Functions (VNFs), to tackle a number of problems: from traffic forecasting for capacity planning and optimization, to the off-line analysis of the daily behavior of metrics to identify possible anomalous patterns, to a Near Real time (NRT) approach for metric prediction and anomaly detection, so to trigger prompt reaction of operators of the infrastructure and services. These problems become particularly challenging in the context of the Vodafone infrastructure, spanning across several data centers for NFV throughout a dozen European Countries.