Machine learning-based actuation orchestration for inter-/intra-data center networks

Abstract

Datacenter (DC) infrastructures are essential to support the requirements posed by nowadays digital society and emerging industrial trends. In such context, a proper actuation management has become especially relevant for service quality assurance operations. In situations where it may be difficult to determine which is the sub-system that needs to apply an actuation, machine learning (ML)-based strategies become valuable assets to orchestrate the actuations to be applied. In this paper, we discuss three strategies for actuation orchestration in inter-/intra-DC scenarios interconnected through optical network systems and benchmark them in terms of requirements that they impose and the achieved performance