Online Cloud Resource Allocation and Pricing with Server Speed Scaling

Abstract

The provisioning of cloud computing services typically incurs huge electricity costs. Utilization maximization of the cloud resources and efficient resource pricing have been key factors determining a cloud provider's revenue. On the other hand, dynamic CPU speed scaling has been widely supported by modern operating systems and hypervisors as an efficient technique for CPU energy saving, potentially useful for cutting down provider's electricity bill. In this paper, we propose an online mechanism for resource allocation and pricing on a cloud platform, which enables dynamic CPU speed scaling for achieving the best job execution efficiency. Using a novel compact infinite optimization technique and the primal-dual online algorithm design framework, our online mechanism achieves computational efficiency, truthfulness, and near-optimal social welfare during the long run of the cloud system. Trace-driven simulation studies further demonstrate good performance of our mechanism in realistic settings.