Towards Predictive Self-optimization by Situation Recognition

Abstract

Energy efficiency of software is an increasingly important topic. To achieve energy efficiency, a system should automatically optimize itself to provide the best possible utility to the user for the least possible cost in terms of energy consumption. To reach this goal, the system has to continuously decide whether and how to adapt itself, which takes time and consumes energy by itself. During this time, the system could be in an inefficient state and waste energy. We envision the application of predictive situation recognition to initiate decision making before it is actually needed. Thus, the time of the system being in an inefficient state is reduced, leading to a more energyefficient reconfiguration.