On the interplay of dynamic voltage scaling and dynamic power management in real-time embedded applications

Abstract

Dynamic Voltage Scaling (DVS) and Dynamic Power Management (DPM) are two popular techniques commonly employed to save energy in real-time embedded systems. DVS policies aim at reducing the CPU energy, while DPM-based solutions involve putting the system components (e.g. memory or I/O devices) to low-power/sleep states at run-time, when sufficiently long idle intervals can be predicted. Despite numerous research papers that tackled the energy minimization problem using DVS or DPM separately, the interactions of these two popular techniques are not yet well understood. In this paper, we undertake an exact analysis of the problem for a real-time embedded application running on a DVS-enabled CPU and using potentially multiple devices. Specifically, by adopting a generalized system-level energy model and taking into account the non-trivial time/energy overheads involved in device transitions, we characterize the variations in different components of the system energy as a function of the CPU processing speed. Then, we propose a provably optimal algorithm to determine the optimal CPU speed as well as device state transition decisions to minimize the system-level energy. Our algorithm runs in O(m log m) time, where m is the number of devices used by the application. The evaluations with realistic system parameters indicate that our solution, which combines DVS and DPM optimally, can lead to substantial energy savings when compared to previous solutions.