Capacity planning for data center to support green computing

We propose a data center resource management framework to support green computing. This framework is composed of the power and workload management, and capacity planning schemes. While an action of power and workload management is performed in a short-term basis (e.g., fraction of minute), a decision of capacity planning is made in a long-term basis (e.g., few months). This paper mainly addresses a capacity planning problem. With the power and workload management, we formulate a capacity planning optimization as a stochastic programming model. The solution is the number of servers to be installed/deployed in a data center over multiple periods. The objective of this optimization model is to minimize the long-term cost under workload demand uncertainty. From the performance evaluation, with the proposed optimization model for the capacity planning scheme, the total cost to operate the data center in the long-term basis can be minimized while the job waiting time and job blocking probability are maintained below the target thresholds.