An integrated approach for applying dynamic voltage scaling to hard real-time systems

Wireless and portable devices depend on the limited power supplied by the battery. Dynamic Voltage Scaling (DVS) is an effective method to reduce CPU power consumption. For real-time systems, DVS algorithms must not only provide enough CPU cycles, but also guarantee that no job misses its deadline. In this paper we propose an integrated approach for applying DVS to real-time systems. We define two functions, the available cycle function (ACF) and the required cycle function (RCF), to capture the CPU workload of the real-time tasks. We then formulate the DVS scheduling problem for real-time systems as a nonlinear optimization problem and propose an optimal off-line algorithm to solve this problem. We also propose a novel online algorithm with time complexity O(1) to further reduce power consumption when a job uses fewer execution cycles than the worst-case budget. The algorithms in this paper are based solely on ACF and RCF, and may be applied to different scheduling policies. We illustrate the generality of our approach over previous research by applying our method to EDF and RM scheduling policies and deriving the optimal off-line DVS algorithms for them. Our simulation results show significant improvement over previous work.