In this paper, we consider simultaneously energy consumption and resource synchronization in mixed-criticality (MC) single processor systems. First, we give a feasibility analysis of single processor systems that execute real-time MC tasks. Second, an energy efficient speed based on sufficient feasibility condition is computed. In addition, we propose a single speed energy efficient algorithm for MC tasks with shared resources (ASS). The ASS algorithm scheduling tasks with $S_{LO}$ is too conservative with much room to save more energy. For energy efficiency, dual speeds scheduling algorithm (DSS) based on ASS algorithm is proposed. It schedules tasks at $S_{LO}$ with blocking and $S_{LO}^{\prime }$ without blocking. Blocking means that the higher priority tasks cannot preempt the execution of current low-priority tasks because low-priority tasks occupy the shared resources required for the higher priority tasks. Moreover, we prove that the DSS algorithm is feasible. Finally, the real-life synthetic application and extensive simulation are applied to validate the proposed algorithm. The experimental results show that the DSS algorithm can reduce energy consumption up to 11.82% compared with the existing approaches.

在本文中，我们同时考虑了混合临界 (MC) 单处理器系统中的能耗和资源同步。首先，我们对执行实时 MC 任务的单处理器系统进行了可行性分析。其次，计算基于充分可行性条件的节能速度。此外，我们为具有共享资源（ASS）的 MC 任务提出了一种单速节能算法。ASS算法调度任务 ${秒}_{升哦}$太保守了，节省更多能源的空间很大。为了提高能效，提出了基于ASS算法的双速调度算法（DSS）。它安排任务在 ${秒}_{升哦}$ 与阻塞和 ${秒}_{升哦}^{\prime }$没有阻塞。阻塞是指高优先级任务不能抢占当前低优先级任务的执行，因为低优先级任务占用了高优先级任务所需的共享资源。此外，我们证明了DSS算法是可行的。最后，应用现实生活中的综合应用和广泛的模拟来验证所提出的算法。实验结果表明，与现有方法相比，DSS算法可以降低高达11.82%的能耗。