Forecast-Assisted NFV Service Chain Deployment Based on Affiliation-Aware vNF Placement

This paper studies the problem of service chain (SC) deployment. Specifically, we try to place virtual network functions (vNFs) on network nodes and connect the vNFs in sequence through link mapping. We start with the offline problem. An integer linear programming (ILP) model is formulated to minimize the total SC deployment cost. With the ILP, we prove that the offline problem is NP-hard and propose a time-efficient heuristic based on affiliation-aware vNF placement. Then, we move to the online problem, and design a forecast-assisted online SC deployment algorithm that includes the prediction of future vNF requirements. Simulation results show that the online algorithms can reduce the blocking probability of SC requests and increase the service provider's profit from SC deployment effectively.