Automatic Resource Provisioning: A Machine Learning Based Proactive Approach

Abstract

This paper concerns dynamic provisioning of cloud resources performed by an intermediary enterprise that provides a private cloud (also referred to as a virtual private cloud) for a single client enterprise using resources acquired on demand from a public cloud. A new proactive technique for auto-scaling of resources that changes the number of resources for the private cloud dynamically based on system load is proposed. The technique that supports both on-demand and advance reservation requests uses machine learning to predict future workload based on past workload. Experimental results demonstrate that the proposed technique can effectively lead to a profit for the intermediary enterprise as well as a reduction of cost for the client enterprise.