探索大规模基于可再生能源的模块化数据中心的高效性
Exploring the Efficiency of Renewable Energy-based Modular Data Centers at Scale
AI总结：
针对可再生能源波动导致模块化数据中心性能下降的问题，提出SkyBox框架，通过变异系数和子图识别算法选择互补能源农场，并实现智能工作负载调度，有效降低了碳排放并减少了对云虚拟机的影响。
摘要：
可以直接部署在能源农场旁且主要由可再生能源供电的模块化数据中心（MDCs），已被证明是降低数据中心碳足迹的一种灵活且有效的方法。然而，使用可再生能源面临的主要挑战是发电量的高度可变性，这意味着为MDCs中的计算资源供电存在极大的波动性，并且由于任务驱逐和迁移会导致应用性能下降。这给平台运营商在决定MDC部署时带来了挑战。为此，我们提出了SkyBox，这是一个采用整体且基于学习方法的框架，旨在帮助平台运营商探索跨地理区域MDC部署中可再生能源的高效利用。SkyBox的提出基于我们对多种可再生能源农场真实功率轨迹研究的见解——可再生能源生产的可预测性，以及不同可再生能源和地点之间能源生产模式的互补性。基于这些见解，SkyBox首先使用变异系数指标来选择合格的可再生能源农场，并提出了一种子图识别算法，以识别一组具有互补能源生产模式的农场。之后，SkyBox实现了智能的工作负载放置和迁移，以进一步容忍功率波动。我们使用真实功率轨迹和数据中心工作负载进行的实验表明，与当前的MDC部署方法相比，SkyBox的碳排放量最低。SkyBox还最小化了功率波动对云虚拟机的影响，使rMDCs成为高效利用可再生能源的实用解决方案。
英文摘要：
Modular data centers (MDCs) that can be placed right at the energy farms and powered mostly by renewable energy, are proven to be a flexible and effective approach to lowering the carbon footprint of data centers. However, the main challenge of using renewable energy is the high variability of power produced, which implies large volatility in powering computing resources at MDCs, and degraded application performance due to the task evictions and migrations. This causes challenges for platform operators to decide the MDC deployment. To this end, we present SkyBox, a framework that employs a holistic and learning-based approach for platform operators to explore the efficient use of renewable energy with MDC deployment across geographical regions. SkyBox is driven by the insights based on our study of real-world power traces from a variety of renewable energy farms -- the predictable production of renewable energy and the complementary nature of energy production patterns across different renewable energy sources and locations. With these insights, SkyBox first uses the coefficient of variation metric to select the qualified renewable farms, and proposes a subgraph identification algorithm to identify a set of farms with complementary energy production patterns. After that, SkyBox enables smart workload placement and migrations to further tolerate the power variability. Our experiments with real power traces and datacenter workloads show that SkyBox has the lowest carbon emissions in comparison with current MDC deployment approaches. SkyBox also minimizes the impact of the power variability on cloud virtual machines, enabling rMDCs a practical solution of efficiently using renewable energy.
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