A Power Efficient and Robust Virtual Network Functions Placement Problem

Reducing the CAPEX and OPEX is a major concern for Telecom Operators (TOs): to this extent, Network Function Virtualization (NFV) has been considered a key aspect to virtualize network functions and push them to the NFV Infrastructure. Virtual Network Functions (VNFs) can be deployed as a set of components running on several cooperating Virtual Machines (VMs) inside modern data centers. As a consequence, it becomes crucial for network operators to minimize the power consumption of their NFV infrastructure, by using the minimum set of physical servers and networking equipment subject to the constraints that VNFs impose on the infrastructure in terms of compute, memory, disk and network resources requirements. In this work, we present a joint resources and flow routing assignment problem for VNFs placement, with the objective of minimizing both the power consumption of the servers and switches needed to deploy the overall virtualized infrastructure and the routing graph. In contrast to many existing works assuming perfect knowledge on input parameters, such as VNFs CPU demands, which is difficult to predict, we propose a novel mathematical model based on the Robust Optimization (RO) theory to deal with data uncertainty. Our numerical evaluation focuses on a specific use-case, that is the deployment of a virtualized Evolved Packet Core (vEPC), namely the core for next generation mobile networks. We demonstrate that with our model, a vEPC operator can trade-off between two important aspects: the power consumption minimization on one side, and the protection from severe deviations of the input parameters on the other (e.g. the resources requirements).