Virtual Power Meter Supported Power Consumption Prediction of Web Services

Service Oriented Computing SOC is a popular software paradigm that is widely employed in IT industry. SOC uses "services" as the unit of functionality of a software application. The massive wave of SOC applications involve considerable energy consumption of servers, which should not be ignored in large-scale computing environment. When a service requirement can be answered by several web services, the energy consumption for each service to response the service request may be different. When this happens, Web Service Selection (WSS) is often required to choose appropriate services to maximize global energy efficiency of SOC applications. Accordingly, this paper proposes a Virtual Power Meter Supported Power Consumption Prediction method for WSS (VPMSPCP). VPMSPCP facilitates choosing appropriate services to minimize wasteful electrical energy from the overall environment of SOC applications. According to our empirical proof, there is a correlation between the power consumption of a service and the status of the server where this service resides. We take advantage of this discovery to develop VPMSPCP by combining an aggregate multiple regression model with a well-known web service power modeling method. There are mainly two steps to establish VPMSPCP. First, we develop a virtual power meter (VPM) for each server. We use a VPM to estimate the average power of a server under a certain status. Second, we apply the VPM to VPMSPCP to estimate power consumption of a web service according to the current status of the servers where the copies of this service reside. Experiments show that VPMSPCP performs well in improving energy saving in WSS.