Predicting Energy Consumption by Extending the Palladio Component Model

The rising energy demand in data centers and the limited battery lifetime of mobile devices introduces new challenges for the software engineering community. Addressing these challenges requires ways to measure and predict the energy consumption of software systems. Energy consumption is influenced by the resource demands of a software system, the hardware on which it is running, and its workload. Trade-off decisions between performance and energy can occur. To support these decisions, we propose an extension of the meta-model of the Palladio Component Model (PCM) that allows for energy consumption predictions. Energy consumption is defined as power demand integrated over time. The PCM meta-model is thus extended with a power consumption model element in order to predict the power demand of a software system over time. This paper covers two evaluations for this meta-model extension: one for a Java-based enterprise application (SPECjEnterprise2010) and another one for a mobile application (Runtastic). Predictions using an extended PCM meta-model for two SPECjEnterprise2010 deployments match energy consumption measurements with an error below 13 %. Energy consumption predictions for a mobile application match corresponding measurements on the Android operating system with an error of below 17.2 %.