Adaptive Resource Provisioning based on Application State

Abstract

Infrastructure providers employing Virtual Network Functions (VNFs) in a cloud computing context need to find a balance between optimal resource utilization and adherence to agreed Service Level Agreements (SLAs). Tenants should be allocated as much computing, storage and network capacity as they need in order not to violate SLAs, but not more so that the infrastructure provider can accommodate more tenants to increase revenue. This paper presents an optimizer VNF that ensures that a given virtual machine (VM) is sufficiently utilized before directing traffic to another VM, and an orchestrator VNF that scales the number of VMs up or down as needed when workloads change, thereby limiting the number of active VMs to a minimum that can deliver the service. We setup a testbed to transcode and stream Video on Demand (VoD) as a service. We present experimental results which show that when the optimizer and orchestrator are used together they outperform static provisioning in terms of both resource utilization and service response times.