An Extended Simple Power Consumption Model for Selecting a Server to Perform Computation Type Processes in Digital Ecosystems

In information systems, applications are required to be realized in the digital ecosystems, high performance systems, and scalable systems. In these applications, a client first selects a server in a cluster of servers and issues a request to the server. The request is performed as a process in the server. In this paper, we consider a computation process which mainly consumes the central processing unit (CPU) resources. Cooling devices, such as fans, consume the electric power in addition to the CPU of a server. The rotation speed of a fan is revved up in servers in order to decrease the temperature of a server. Thus, the total power consumption of a server depends on not only computational devices such as a CPU, but also cooling devices. We discuss an extended simple power consumption (ESPC) model of a server with a multicore CPU and cooling devices to perform computation type processes. It is critical to discuss how to select a server for each request issued by a client in order to not only achieve performance objectives, but also reduce the total power consumption of a system based on the ESPC model. An improved power consumption laxity-based (IPCLB) algorithm for selecting a server is proposed in this paper, where the minimum power to be consumed is used to perform the process. We evaluate the ESPC model and IPCLB algorithm in terms of power consumption and elapse time.