Online Joint VNF Chain Composition and Embedding for 5G Networks

Network function virtualization (NFV) is one of the enabling technologies for fifth generation (5G) networks. How to allocate physical resources to customized network services both fairly and efficiently remains a challenging research issue in NFV. This paper proposes a two-stage approach to jointly optimize the chaining and embedding of virtual network functions (VNFs), to obtain feasible composition and embedding results with low complexity, while the average embedding cost is minimized and the total revenue is increased. In the first stage, the VNF chaining order is optimized based on the location and functionality of substrate nodes, and the ratio of outgoing data rate over incoming data rate for each required VNF. In the second stage, we allocate the physical resources based on the preliminary VNF ordering under the resource capacity constraints. A node splitting mechanism is also employed to improve the resource allocation fairness and increase the service acceptance ratio for the substrate network. Simulation results are presented to validate the feasibility and effectiveness of the proposed approach.