Fine-Grained Cloud Resource Provisioning for Virtual Network Function

Abstract

The deployment of Virtualized Network Functions is expected to be dynamic and swift when using Network Function Virtualization technology. The dynamic nature of workload from users requires the resource allocation of underlying infrastructure to be flexible to cope with the changes. Existing works investigated elastic NFV solutions by dynamically creating and dismantling Virtual Machine (VM) replicas, while maintaining balanced workload among VMs. However, those solutions are coarse-grained which may cause unnecessary resource over-provisioning as different network functions consume different amount of resources. In this paper, we present ElasticNFV, a dynamic and fine-grained cloud resource provisioning solution for VNF. ElasticNFV takes real-time resource demand of multiple service chains and allocates resources through an elastic provision mechanism. When a scaling conflict occurs, ElasticNFV provides a two-phase minimal migration algorithm to optimize the migration time and embedding cost of VNF instances. We implement ElasticNFV on top of the KVM platform to provide elastic VM for each VNF instance and Open vSwitch to form elastic intra-cloud network with virtual links between VNF instances. Our evaluation results show that ElasticNFV can improve VNF performance significantly, and achieve high resource utilization and fast migration time with low cost.