Virtual network function placement and resource optimization in NFV and edge computing enabled networks
Abstract Network function virtualization (NFV) and edge computing (EC) are two promising and innovative technologies to accelerate 5G networks. However, placing the service function chains (SFC), each of which consists of a series of ordered virtual network functions (VNFs), into the EC enabled networks is an intractable issue and some new challenges shall arise. Firstly, EC is a hierarchical and geo-distributed structure, which will influence the form of SFCs and make the VNF placement location-related. Secondly, the data processing in EC is hierarchical too, which incurs different latency requirements. In this paper, we study the VNF placement problem considering users’ SFC requests (SFCr) in NFV and EC enabled networks. Apart from the above new challenges, the implementation method and chaining of VNFs are also considered, which will raise the need of tradeoff between node resource consumption and bandwidth consumption when placing VNFs. Then the above problem is formulated as an integer linear programming (ILP) model mathematically aiming to minimize the total resource consumption, which is proven to be NP-hard. We get the optimal results when the number of SFCrs is small taking advantage of optimization solver and propose a polynomial time heuristic when the problem scale is large. Simulation results show that the resource consumption derived by our heuristic solution is near to the optimal solution and its performance is very much superior to the contrastive schemes.