Elastic Network Service Chain with Fine-grained Vertical Scaling

By moving network functions from dedicated hardware to software, Network Function Virtualization (NFV) is expected to bring the advantages of cloud computing to network management. Frequent workload changes require the underlying infrastructure to be dynamic and agile to cope with the changes. Some existing studies have investigated elastic virtual machine (VM) positioning solutions by dynamically creating and destroying VM replicas, while maintaining balanced workload among VMs. However, those solutions are coarse-grained which may cause unnecessary resource over-provisioning and low resource utilization. In this paper, we propose ElasticNFV, a dynamic solution that achieves fine-grained cloud resource provisioning for Virtual Network Functions (VNFs). ElasticNFV analyzes realtime resource demand of multiple service chains and allocates resource through an elastic provision mechanism. When a scaling conflict occurs, ElasticNFV provides a Two-Phase Minimal Migration (TPMM) algorithm to optimize migration time and embedding cost of VNFs based on prediction. We implemented ElasticNFV on top of a KVM virtualization platform and Open vSwitch. Through simulation and testbed evaluation, we show that ElasticNFV can achieve high resource utilization and short migration time with low cost.