This paper presents a novel approach to characterise applications with respect to their energy consumption by using a set of energy-related metrics, called Green Metrics. These indicators are based on energy consumption measurements, such as indexes of computing resource usage, of environmental impact, and even of development costs required to (re)design an application in order to optimise its energy consumption footprint, or of organizational factors related to application management. Our approach is framed in the GAMES (Green Active Management of Energy in IT Service centres) EU Project1 about green IT. In this paper, we define four clusters of Green Metrics enabling to feature an application in terms of the energy it consumes at run time. Such metrics are the basis for measuring the "greenness" of an application and to detect where it consumes and wastes energy. Hints are provided to improve applications design and execution. We show within an application scenario how monitoring and evaluation of the Green Metrics helps to improve energy efficiency.

In this paper we propose an energy aware dynamic consolidation algorithm for virtualized service centers based on reinforcement learning. The energy awareness is enacted by using the Energy Aware Context Model (EACM) to programmatically represent the current service center context situation by means of ontologies. We have defined the EACM model entropy metric for evaluating the service center greenness level. If the entropy value is above a predefined threshold, the service center is not in a green state. As a consequence, consolidation or dynamic power management actions are selected by means of reinforcement learning and executed to bring back the service center in an energy efficient state. The results are promising showing that the proposed energy aware consolidation algorithm decreases the energy consumption with about 26% from the total energy consumption of a service center.