Abstract: Low energy consumptions are extremely important in real-time embedded systems. Due to the uncertainties in execution time of some tasks, this paper models each varied execution time as a probabilistic random variable and incorporating applications' performance requirements to explore real-time embedded systems and avoid over-designing them. We propose a practical algorithm to minimize the expected value of total energy consumption while satisfying the timing constraint with a guaranteed confidence probability. The experimental results show that our approach achieves significant energy saving than previous work. For example, our algorithm achieves an average improvement of 61.2% on total energy consumption compared with the algorithm in previous work.