On multicore platforms, reliable task execution, as well as low energy consumption, are essential. Dynamic Voltage/Frequency Scaling (DVFS) is typically used for energy savings, but with a negative impact on reliability, especially when the applied frequency is low. Using high frequencies, required to meet reliability constraints, or replicating tasks increases energy consumption. To reduce energy consumption, while enhancing reliability and satisfying real-time constraints, we propose a hybrid approach that combines distinct reliability enhancement techniques, under task-level, processor-level and system-level DVFS. Our task mapping problem jointly decides task allocation, task frequency assignment, and task duplication, under real-time and reliability constraints. This is achieved by formulating the task mapping problem as a Mixed Integer Non-Linear Programming problem, and equivalently transforming it into a Mixed Integer Linear Programming, that can be optimally solved. From the obtained results, the proposed approach achieves better energy consumption, finding solutions, when replication approaches fail.

在多核平台上，可靠的任务执行以及低能耗至关重要。动态电压/频率缩放 (DVFS) 通常用于节能，但会对可靠性产生负面影响，尤其是在应用频率较低时。使用满足可靠性限制或复制任务所需的高频会增加能耗。为了降低能耗，同时提高可靠性并满足实时约束，我们提出了一种混合方法，该方法在任务级、处理器级和系统级 DVFS 下结合了不同的可靠性增强技术。我们的任务映射问题在实时和可靠性约束下共同决定任务分配、任务频率分配和任务重复。这是通过将任务映射问题公式化为混合整数非线性规划问题，并将其等效地转换为可以优化解决的混合整数线性规划问题来实现的。从获得的结果来看，当复制方法失败时，所提出的方法可以实现更好的能源消耗，找到解决方案。