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 by adjusting CPU voltage. For real-time systems, DVS algorithms must 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 under a scheduling policy. 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 complexityÇ 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. When ACF and RCF are defined, the algorithms can be applied to any scheduling policy. We illustrate the generality of our approach over previous research by applying our method to several scheduling policies, including FIFO, EDF and RM. Our simulation results show significant improvement over previous work.