论文标题

黄瓜:可再生能感知的延迟云和边缘工作负载的录取控制

Cucumber: Renewable-Aware Admission Control for Delay-Tolerant Cloud and Edge Workloads

论文作者

Wiesner, Philipp, Scheinert, Dominik, Wittkopp, Thorsten, Thamsen, Lauritz, Kao, Odej

论文摘要

云和边缘计算的电力需求不断增长会增加运营成本,并将很快对环境产生重大影响。可能的对策是将IT基础设施与现场可再生能源直接装备。但是,尤其是较小的数据中心可能无法始终直接使用所有生成的功率,而将其馈入公共网格或能源存储通常不是一个选择。为了最大程度地利用可再生能源的使用,我们提出了Cucumber,这是一种录取控制政策,仅当可以在其截止日期内计算而无需使用电网能量时,才能接受延迟耐受性工作负载。使用计算负载,能源消耗和能源产生的概率预测,可以将Cucumber配置为更乐观或保守的入院。我们在模拟环境中使用对柏林,墨西哥城和开普敦的实际太阳能生产预测进行了两种情况评估我们的方法。对于实际可用的过量能量的情况,我们的结果表明,黄瓜的默认配置达到了接近最佳情况的接受率,并导致97.0%的接受工作负载使用过多的能量供电,而更保守的录取率会导致18.5%的接收能力在几乎零网格功率下降低。

The growing electricity demand of cloud and edge computing increases operational costs and will soon have a considerable impact on the environment. A possible countermeasure is equipping IT infrastructure directly with on-site renewable energy sources. Yet, particularly smaller data centers may not be able to use all generated power directly at all times, while feeding it into the public grid or energy storage is often not an option. To maximize the usage of renewable excess energy, we propose Cucumber, an admission control policy that accepts delay-tolerant workloads only if they can be computed within their deadlines without the use of grid energy. Using probabilistic forecasting of computational load, energy consumption, and energy production, Cucumber can be configured towards more optimistic or conservative admission. We evaluate our approach on two scenarios using real solar production forecasts for Berlin, Mexico City, and Cape Town in a simulation environment. For scenarios where excess energy was actually available, our results show that Cucumber's default configuration achieves acceptance rates close to the optimal case and causes 97.0% of accepted workloads to be powered using excess energy, while more conservative admission results in 18.5% reduced acceptance at almost zero grid power usage.

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