Placement and Allocation of Virtual Network Functions: Multi-Dimensional Case

Abstract

With the gradual transitioning to Network function virtualization (NFV), Internet service providers face the problem of where to introduce NFV in order to make the most benefit of that; here, we measure the benefit by the amount of traffic that can be served in an NFV-enabled network. This problem is non-trivial as it is composed of two challenging subproblems: 1) placement of nodes to support virtual network functions (referred to as VNF-nodes); 2) allocation of the VNF-nodes' resources to network flows. This problem has been studied for the one-dimensional setting, where all network flows require one network function, which requires a unit of resource to process a unit of flow. In this work, we consider the multi-dimensional setting, which introduces new challenges in addition to those of the one-dimensional setting (e.g., NP-hardness and non-submodularity). To address these difficulties, we propose a novel two-level relaxation method that allows us to draw a connection to the sequence submodular theory and utilize the property of sequence submodularity along with the primal-dual technique to design two approximation algorithms. We prove that the proposed algorithms have a non-trivial approximation ratio and perform trace-driven simulations to show the effectiveness of the proposed algorithms.