Energy-Aware Distributed Systems for Computation and Storage-Based Applications

The electric power consumption of servers has to be reduced in information systems in addition to increasing the performance and fault-tolerancy in order to realize green societies. In information systems, servers mainly consume the electric power to perform processes requested by clients. We consider computation (CP) and storage (ST) types of application processes to be performed on servers. In CP processes, CPU resource is mainly consumed. In s_t processes, storage drives are manipulated in a server. First, we present the storage-based power consumption (SBPC) model of a server st to perform s_t and CP processes. The SBPC model is a four-state model, where the power consumption rate of the server is one of four rates minE_t, maxST_t, maxC_t, and maxSTC_t. Here, the power consumption rate E_t(τ) of a server st of time τ is minimum minE_t if no process is performed. E_t(τ) the power consumption rate is maxST_t if only and at least one ST process is performed. E_t(τ) is maxC_t if only and at least one CP process is performed on the server s_t. If both ST and CP processes are performed, E_t(τ) is maxSTC_t. Here, minE_t <; maxST_t <; maxC_t <; maxSTC_t. According to the SBPC model, it is better not to perform both ST and CP processes on a same server because the maximum power is consumed in the server. By using the SBPC model, we discuss an algorithm for selecting a server so that not only the execution time but also the power consumption can be reduced. In the algorithm, ST and CP processes are tried to be performed on different servers.