Abstract
It is critical to reduce the electric power consumed by servers in a cluster in order to realize eco society. In our previous studies, the multi-level power consumption (MLPC) model of a server with a multi-thread CPU, the power consumption of the server is proposed and the globally energy-aware (GEA) algorithm is discussed to select a server for each process in a cluster. Here, not only the total electric energy consumption of all the servers but also the ratio of the basic electric energy consumed by the servers to the total electric energy consumption can be reduced in a cluster. However, the GEA algorithm is not scalable since every server is checked to find a server for each process in a cluster. In this paper, we newly propose a scalable energy-aware (SEA) algorithm to select a server for a process. Here, some number of servers are first randomly selected in a cluster and one server is then selected in the selected servers by the GEA algorithm. We evaluate the SEA algorithm and show not only the total electric energy consumption of the servers but also the average execution time of processes are reduced in the SEA algorithm compared with other algorithms.
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