Resource Provisioning for Virtual Network Function Deployment with In-Subnetwork Processing

Network Function Virtualization (NFV) is an efficient approach to simplify and accelerate the deployment of diverse network services. In this paper, we study the problem of link capacity and server purchase to provision the network which enables joint Virtual Network Function (VNF) placement on servers and traffic engineering in a network spanning multiple subnetworks. Each subnetwork is owned and controlled by a different administrator. Given flow demands, we formulate the problem from a sparse optimization perspective and propose an efficient approach based on iteratively solving a sequence of group LASSO problems. Using purchased link capacities and servers, each subnetwork is able to carry out VNF placement and traffic engineering locally to meet flow demands. A scalable and decentralized approach based on the proximal Alternating Direction Method of Multipliers (ADMM) is proposed for this problem. The distributed optimization can be locally solved with minimum information shared with other administrators. Extensive numerical evaluations show the efficiency of our approach against existing work.