Evaluation of the Algorithms for Selecting an Energy-efficient Storage Server in Storage and Computation Oriented Applications

The electric power consumed by servers has to be reduced in order to realize green societies. We consider computation (CP) and storage (ST) types of application processes performed on servers in this paper, where CPU and storage drives are mainly consumed, respectively. The authors proposed the storage-based power consumption (SBPC) model and storage-based computation (SBCP) model to perform ST and CP processes on a server. Here, the power consumption rate Et( ) [W] of a server st at time depends on types of processes which are concurrently performed but is independent of the number of the processes on the server st in the SBPC model. The average execution time of a CP process depends on the numbers of CP processes concurrently performed and the average execution time of an ST process depends on the number of concurrent ST and CP processes in the SBCP model. By using the SBPC and SBCP models, we enhance the energy aware (EA) algorithm for selecting a server for each CP/ST process so that not only the execut n time of each process but also the power consumption of servers can be reduced. We show the evaluation of the EA algorithm in terms of the total power consumption and average execution time. Keywords-Power consumption models, Energy-aware (EA) selection algorithm, Storage-based power consumption (SBPC) model, Storage-based computation (SBCP) model.