Application Execution Time Prediction for Effective CPU Provisioning in Virtualization Environment

Abstract

Provisioning of hardware resources through virtual machines (VMs) has been widely used for supporting server consolidation and infrastructure-as-a-cloud computing. We propose NICBLE to support accurate CPU resource provisioning for application workload running on VMs. While CPU is essential for any application workload, not every workload requires the same level of CPU resource. The VM tenants may also have different expectations of application performance and preferences. NICBLE models the execution of an application workload and employs a simulation-based algorithm to predict the impact on application execution time for a hypothetical VM configuration change on the number of CPUs. One may use NICBLE to reason about whether changing the number of CPUs will significantly affect the application performance. We built the NICBLE prototype on top of the Xen hypervisor [1]. NICBLE does not require modification to the guest systems. The performance overhead on the guest system is negligible. Our evaluation indicates that NICBLE is able to provide accurate prediction with an average error rate of less than 15 percent for non-adaptive application workload.