边缘计算在处理大量计算复杂的任务时，可能会引发任务实时执行效果下降以及能耗高等方面的问题。为此提出一种面向边云协同计算的能耗感知资源调度方法，首先根据实时保证率将任务分流到云计算和边缘计算，然后基于弹性资源特性提出能耗感知的资源调度策略，为实时任务生成虚拟资源配置方案，最后通过仿真实验验证了所提算法的有效性，该算法可以在保证实时性的前提下降低能耗。
An energy-aware resource scheduling method for edge-cloud collaborative computing is proposed to address the issues of degraded real-time execution performance and high energy consumption when processing computationally complex tasks in edge computing. First, tasks are assigned to cloud computing and edge computing according to the real-time guaranteed rate. Then, an energy-aware resource scheduling strategy is proposed based on elastic resource characteristics to generate virtual resource configuration schemes for real-time tasks. Finally, simulation results verify the effectiveness of the proposed algorithm, which reduces energy consumption while ensuring real-time performance.
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