Minimizing Multi-resource Energy for Real-Time Systems with Discrete Operation Modes

Energy conservation is an important issue in the design of embedded systems. Dynamic Voltage Scaling (DVS) and Dynamic Power Management (DPM) are two widely used techniques for saving energy in such systems. In this paper, we address the problem of minimizing multi-resource energy consumption concerning both CPU and devices. A system is assumed to contain a fixed number of real-time tasks scheduled to run on a DVS-enabled processor, and a fixed number of off-chip devices used by the tasks during their executions. We will study the non-trivial time and energy overhead of device state transitions between active and sleep states. Our goal is to find optimal schedules providing not only the execution order and CPU frequencies of tasks, but also the time points for device state transitions. We adopt the frame-based real-time task model, and develop optimization algorithms based on 0-1 Integer Non-Linear Programming (0-1 INLP) for different system configurations. Simulation results indicate that our approach can significantly outperform existing techniques in terms of energy savings.