A Scalable and Distributed Approach for NFV Service Chain Cost Minimization

Abstract

Network function virtualization (NFV) represents the latest technology advancement in network service provisioning. Traditional hardware middleboxes are replaced by software programs running on industry standard servers and virtual machines, for service agility, flexibility, and cost reduction. NFV users are provisioned with service chains composed of virtual network functions (VNFs). A fundamental problem in NFV service chain provisioning is to satisfy user demands with minimum system-wide cost. We jointly consider two types of cost in this work: nodal resource cost and link delay cost, and formulate the service chain provisioning problem using nonlinear optimization. Through the method of auxiliary variables, we transform the optimization problem into its separable form, and then apply the alternating direction method of multipliers (ADMM) to design scalable and fully distributed solutions. Through simulation studies, we verify the convergence and efficacy of our distributed algorithm design.