Embedding Virtual Network Functions with Backup for Reliable Large-Scale Edge Computing

To support real-time edge computing in urban area, a number of edge servers are deployed for end devices to provide computing and storage services. Considering the massive and diverse computing requests from end devices, Network Function Virtualization (NFV) is employed for flexible service management at the edge servers. In this paper, we investigate an essential problem in NFV for large-scale edge computing – Virtual Network Function Embedding (VNFE) problem, which is NP-hard. While backup is an important means to improve the availability, we focus on the VNFE problem with backup and jointly consider the impacts of network functions/facilities. The problem is formalized as a non-linear 0-1 programming problem. We then propose a heuristic embedding algorithm based on the impacts estimation for both network functions and facilities, in which the embedding of critical Virtual Network Functions (VNFs) and servers are prioritized. We implement the algorithm and conduct extensive simulation experiments. The results show that the proposed work can greatly improve availability and resource utilization for large-scale edge computing.