Load forecasting applied to soft real-time web clusters

Abstract

Dynamic configuration techniques such as DVFS (Dynamic Voltage and Frequency Scaling) and turning on/off computers are well known ways to promote energy consumption reduction in web server clusters. This paper demonstrates how the application of forecasting methods improves energy savings in a soft real-time application, and compares it with other energy aware methods. Instead of a synthetic workload, a real traffic pattern was used to make the experiments more realistic. Our system promotes energy reduction while maintaining user's satisfaction with respect to deadlines being met. The results obtained show that prediction capabilities increase the QoS of the system, while maintaining or improving the energy savings over state-of-the-art power management mechanisms.