SLA-driven dynamic resource provisioning for service provider in cloud computing

Cloud Computing provides a convenient means of remote and pay-per-use access to computing resources in forms of Virtual Machines (VMs). Specially, with cloud computing, service providers no longer need to maintain a large number of expensive physical machines, which can significantly reduce the cost. However, due to the fluctuation and uncertainty of the future demands, it is still a challenge for service providers to dynamically determine the optimal resource provisioning to save cost while guaranteeing the Service Level Agreement (SLA). Overload may result in the service unavailable for the latter service requests while over-provisioning naturally increases the cost. To address the problem, in this paper, by defining the unavailability probability of the service as a metric of SLA, we propose a SLA-driven dynamic VMs provisioning strategy based on the large deviation principle, which is capable of proactive calculating the optimal number of VMs for the upcoming demands subject to the unavailability probability below a desired threshold. Finally, the experiments are performed based on real workload traces to show the attainable performance of the proposed resource provisioning strategy and verify that the proposed strategy can make a good tradeoff between saving cost and guaranteeing SLA.