An Efficient Service Function Chain Placement Algorithm in a MEC-NFV Environment

Mobile Edge Computing (MEC) is a promising network architecture that pushes network control and mobile computing to the network edge. Recent studies propose to deploy MEC applications in the Network Function Virtualization (NFV) environment. The mobile network service in NFV is deployed as a Service Function Chains (SFC). In this paper, we solve the SFC placement problem in a MEC-NFV environment. We formulate the SFC placement problem as a weighted graph matching problem, including two sub-problems: a graph matching problem and a SFC mapping problem. To efficiently solve the graph matching problem, we propose a linear programming-based approach to calculate the similarity between physical nodes and VNFs. Based on the similarity, we design a Hungarian-based placement algorithm to solve the SFC mapping problem. Evaluation results show that our proposed solutions outperform the greedy algorithm in terms of execution time and resource utilization.