Optimal update frequency model for physical machine state change and virtual machine placement in the cloud

Cloud computing is evolving into the default operational framework running modern data centers. Efficient data center operation is concerned with the total amount of energy consumed as well as assuring adequate resources are available to process all of the incoming work requests. Existing research has demonstrated several algorithms that can be used to determine the optimal number of resources required to service these requests. However, a key issue not addressed in these algorithms is determining the frequency of recalculating the number of required resources. Changing the required resources at a rate slower than the optimal update frequency results in lower energy efficiency due to the over allocation of resources. Changing the resources at a rate higher than the optimal frequency results in insufficient time for systems to change state, which results in SLA violations. In this paper, a stochastic optimization model is presented that determines the optimal update frequency for changing the states of the nodes of the cloud as well as determining the proper frequency for recalculating the maximum expected load, which improves the determination of the optimum number of resources required, therefore maximizes energy efficiency and minimizes SLA violations.