dynamic power management in environmentally powered systems
In this paper a framework for energy management in energy harvesting embedded systems is presented. As a possible example scenario, we focus on wireless sensor nodes which are powered by solar cells. We demonstrate that classical power management solutions have to be reconceived and/or new problems arise if perpetual operation of the system is required. In particular, we provide a set of algorithms and methods for different application scenarios, including real-time scheduling, application rate control as well as reward maximization. The goal is to optimize the performance of the application subject to given energy constraints. Our methods optimize the system performance which allows the usage of, e.g., smaller solar cells and smaller batteries. Our theoretical results are supported by simulations using long-term measurements of solar energy in an outdoor environment. Furthermore, to demonstrate the practical relevance of our approaches, we measured the implementation overhead of our algorithms on real sensor nodes.
power management energy harvesting embedded systems real-time scheduling reward maximization model predictive control