Global EDF-based online, energy-efficient real-time scheduling in multi-core platform

As the energy consumption becomes increasingly prominent, how to meet time constraints while reducing the energy consumption as much as possible is a fundamental problem of the real-time scheduling in multi-core systems. Most of the existing energy-efficient scheduling approaches make assumptions on the properties of the scheduled tasks. In general, the properties of a task are unknown in advance until the task arrives. Thus, these approaches for deterministic tasks are not suitable to the general tasks. To schedule general tasks without prior knowledge of their properties, we propose an online and energy-efficient scheduling algorithm, based on Global Earliest Deadline First, for hard real-time tasks in multi-core processor platform. We propose a novel approach to decrease the execution frequency of tasks, and achieve a reasonable compromise between the time constraint and saved energy. This is ensured by utilizing the slack time of tasks and the dynamic voltage/frequency scaling techniques. The evaluation results show that our algorithm is well applied to the two types of dynamic voltage/frequency scaling techniques, and out-performs the Global EDF algorithm in terms of the saved energy. Specifically, our algorithm improves the saved energy of the Global EDF algorithm by at most 10% to 15% under real discrete dynamic voltage/frequency scaling levels.