VNF Placement over Autonomic Elastic Optical Network via Deep Reinforcement Learning

Orchestration of computing and network resources across multiple technology layers is critical for the autonomous roll-out of network services that fulfill the heterogeneous requirements of vertical industries. Therefore, effectively mapping the requirements of verticals into underlying infrastructure management decisions is a challenging issue. In this paper, we evaluate the provisioning of vertical-driven network services, composed of a set of interconnected virtual network functions, on top of a distributed cloud infrastructure interconnected through an Elastic Optical Network (EON). To this end, we propose a solution exploiting the advantages of Deep Reinforcement Learning. This solution relies on two cooperating agents to execute an efficient selection of computing resources in the cloud infrastructure for the placement of virtualized network functions, as well as the routing and spectrum assignment in the EON. The performance of the proposed solution is evaluated in scenarios where arrival and departure of service requests are dynamic. Experimental results show the improved performance of the proposed solution with and without invalid action masking over a heuristic algorithm in terms of service blocking rate.