事件驱动的应用程序限电:协调高利用率和低尾响应时间

David Desmeurs, C. Klein, A. Papadopoulos, Johan Tordsson
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引用次数: 16

摘要

由于缺乏能源比例和低资源利用率,数据中心目前浪费了大量的能源,后者目前是确保应用程序响应性所必需的。为了解决第二个问题,我们提出了一种新的应用程序级技术,我们称之为事件驱动的Brownout。对于每个请求,例如,以事件驱动的方式,应用程序可以执行一些可选代码,这些代码不是正确操作所必需的,但对于用户体验来说是理想的,并且只有在挂起的客户端请求数量低于给定阈值时才执行。我们提出了几种基于控制理论和机器学习的自主算法,以根据测量的应用程序第95百分位响应时间自动调整该阈值。我们使用RUBiS基准对我们的方法进行了评估,该基准显示,与竞争方法相比,在保持响应时间接近高利用率的设定点方面有11倍的改进。我们的贡献是通过允许应用程序在高资源利用率的情况下保持响应时间接近设定值,从而打开通往更节能的数据中心的道路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Event-Driven Application Brownout: Reconciling High Utilization and Low Tail Response Times
Data centers currently waste a lot of energy, due to lack of energy proportionality and low resource utilization, the latter currently being necessary to ensure application responsiveness. To address the second concern we propose a novel application-level technique that we call event-driven Brownout. For each request, i.e., in an event-driven manner, the application can execute some optional code that is not required for correct operation but desirable for user experience, and does so only if the number of pending client requests is below a given threshold. We propose several autonomic algorithms, based on control theory and machine learning, to automatically tune this threshold based on measured application 95th percentile response times. We evaluate our approach using the RUBiS benchmark which shows a 11-fold improvement in maintaining response-time close to a set-point at high utilization compared to competing approaches. Our contribution is opening the path to more energy efficient data-centers, by allowing applications to keep response times close to a set-point even at high resource utilization.
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