Multi-domain non-cooperative VNF-FG embedding: A deep reinforcement learning approach

Abstract

Network Function Virtualization (NFV) and service orchestration simplify the deployment and management of network and telecommunication services. The deployment of these services require, typically, the allocation of Virtual Network Function - Forwarding Graph (VNF-FG), which implies not only the fulfillment of the service's requirements in terms of Quality of Service (QoS), but also considering the constraints of the underlying infrastructure. This topic has been well-studied in existing literature, however, its complexity and uncertainty unveil many challenges for researchers and engineers. This issue is especially complex when it comes to placing a service on several non-cooperative domains, where the network operators hide their infrastructure to other competing domains. In this paper, we address these problems by proposing a deep reinforcement learning based VNF-FG embedding approach. The results provide insights into behaviors of non-cooperative domains. They also show the efficiency of proposed VNF-FG deployment approach having automatic inter-domain load balancing.