High Availability Deployment of Virtual Network Function Forwarding Graph in Cloud Computing Environments

Abstract

Network Function Virtualization (NFV) stands out quickly as a promising innovation in telecommunication networks. It leverages the concept of cloud technology and virtualization techniques. However, the continuity of cloud network services has become an essential availability requirement for NFV. Failure of Virtual Network Functions (VNFs) may cause critical quality assurance problems for such network services. VNF chaining and placement can be considered as the VNF Forwarding Graph (VNF-FG) mapped on a cloud provider infrastructure, also called NFV Infrastructure (NFVI). This mapping is addressed while neglecting the massive link utilization and bandwidth consumption that can be encountered during VNF recovery phase. In this paper, an Integer Linear Programming (ILP) approach is developed to model VNF-FG deployment problem while guaranteeing high availability against node/VM failures. Then, the Redundant VNF-FG Deployment (RVNF-FGD) heuristic algorithm is proposed that takes VNF migration into consideration. RVNF-FGD algorithm attempts to find a near-optimal solution that achieves a trade-off between availability and scalability with a reasonable convergence time. Thus, facilitating the practical deployment of the proposed approach. Simulation results confirm that RVNF-FGD algorithm is capable of simultaneously reducing link utilization and bandwidth consumption across the core layer of the cloud network. In addition, it reduces VNF-FG communication cost and overall energy consumption. The convergence time of RVNF-FGD algorithm is assessed by applying it to broader cloud network architectures. This assessment indicates the viability of the proposed approach in responding quickly to failures.