Profit-driven resource scheduling for virtualized cloud systems

Abstract

Virtualized resource renting is a key issue in IaaS (Infrastructure-as-a-Service) cloud systems. Suitable resource allocation improves resource utilization and increases profit for application providers. The application provider will obtain better revenues according to the Service Level Agreement (SLA), if they rent more virtual resources. However, they will invest much more capital for renting these virtual resources. How many resources a provider rents has become a key thing for cloud applications. This paper addresses the reconciliation objectives by proposing a profit-driven resource scheduling method for virtualized cloud systems. Compared with traditional methods, our method aims at maximizing the revenues by introducing SLA and the cost of renting cloud resource, instead of increasing resource utilization or decreasing early finishing time. We model the performance of applications with queueing theory; calculate the revenues according to the SLA and renting cost; adjust the amount of virtual resources to adapt to dynamic workloads in period. We have implemented a framework for scheduling virtual resources, and applied it in our IaaS cloud platform OnceCloud. The experimental results demonstrate that our method has advantages over existing ones in revenues.