Renewable and cooling aware workload management for sustainable data centers
Renewable and cooling aware workload management for sustainable data centers
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DOI：
10.1145/2254756.2254779
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发表时间：
2012-06
期刊：
影响因子：
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通讯作者：
Zhenhua Liu;Yuan Chen;C. Bash;A. Wierman;D. Gmach;Zhikui Wang;M. Marwah;C. Hyser
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文献类型：
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作者：
Zhenhua Liu;Yuan Chen;C. Bash;A. Wierman;D. Gmach;Zhikui Wang;M. Marwah;C. Hyser
近期，数据中心计算需求激增，增加了全球数据中心的总能源足迹。数据中心通常由三个子系统组成：信息技术设备为客户提供服务；电力基础设施为信息技术设备和冷却设备提供支持；冷却基础设施用于移除这些子系统产生的热量。这项工作提出了一种对数据中心能量流进行建模并优化其运行的新方法。传统上，能源或冷却可用性等供应方的限制条件是与信息技术工作负载管理分开处理的。这项工作采用一种整体方法，将可再生能源供应、动态定价以及包括制冷机和室外空气冷却在内的冷却供应与信息技术工作负载规划相结合，以降低电力成本和环境影响，从而提高数据中心运营的整体可持续性。具体而言，我们首先预测可再生能源以及信息技术需求。然后，我们利用这些预测来生成一个信息技术工作负载管理计划，该计划根据随时间变化的电力供应和冷却效率来安排数据中心内的信息技术工作负载并分配信息技术资源。我们已经使用来自真实数据中心和生产系统的记录来实施和评估我们的方法。结果表明，与现有技术相比，我们的方法可以将经常性电力成本和不可再生能源的使用量降低多达60%，同时仍然满足服务水平协议。
Recently, the demand for data center computing has surged, increasing the total energy footprint of data centers worldwide. Data centers typically comprise three subsystems: IT equipment provides services to customers; power infrastructure supports the IT and cooling equipment; and the cooling infrastructure removes heat generated by these subsystems. This work presents a novel approach to model the energy flows in a data center and optimize its operation. Traditionally, supply-side constraints such as energy or cooling availability were treated independently from IT workload management. This work reduces electricity cost and environmental impact using a holistic approach that integrates renewable supply, dynamic pricing, and cooling supply including chiller and outside air cooling, with IT workload planning to improve the overall sustainability of data center operations. Specifically, we first predict renewable energy as well as IT demand. Then we use these predictions to generate an IT workload management plan that schedules IT workload and allocates IT resources within a data center according to time varying power supply and cooling efficiency. We have implemented and evaluated our approach using traces from real data centers and production systems. The results demonstrate that our approach can reduce both the recurring power costs and the use of non-renewable energy by as much as 60% compared to existing techniques, while still meeting the Service Level Agreements.