The Network Service Function Chain Scheduled with Non-dominated Sorting Genetic Algorithm IV

Network Function Virtualization (NFV) is a popular technology, among which is Service Function Chain (SFC), a critical technology of modern communication networks. However, SFC needs to pass through multiple nodes to complete the processing of Virtual Network Functions (VNFs), so planning the best routing for SFC to ensure system performance is an important issue. We defined the Multiple Objectives Optimization (MOO) problem for the SFC and Edge Nodes relationship. Meanwhile, the Non-dominated Sorting Genetic Algorithm IV (NSGA-IV) was used, and the effect was compared with the NSGA-III algorithm. The simulation results show that the proposed method is better than NSGA-III in load balancing, latency, and throughput, indicating that our method can effectively improve the operating performance of NFV-SFC.