Demand Response aware cluster resource provisioning for parallel applications

Chen Wang, M. Groot
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引用次数: 3

Abstract

Data center energy consumption is significant and accounts for about 2% of total energy use in the U.S. recently. A range of approaches, from cooling techniques to workload consolidation have been taken to improve data center energy efficiency. In contrast to most methods published so far, this paper treats a data centre as a consumer in an electricity market. Our intention is to make data centres more responsive to electricity market conditions with minimal impact on their performance. In electricity markets, Demand Response(DR) is a method for improving grid efficiency by encouraging consumers to adjust their demand during price peaks or network stress. Significant consumption and cost savings can potentially be made via implementing DR programs involving a large set of consumers. Traditionally, DR has been a largely manual process, however, automated DR is becoming increasingly prevalent due to the deployment of smart grid technologies. In this paper, we treat the server cluster in a data centre as an energy consumer that participates DR activities. We give two algorithms to enable the cluster to automatically adjust the number of active servers to respond to DR requests while maintaining acceptable system performance. We evaluate our algorithms using real traces.
为并行应用程序提供支持需求响应的集群资源供应
数据中心的能源消耗非常大,最近约占美国总能源消耗的2%。从冷却技术到工作负载整合,已经采取了一系列方法来提高数据中心的能源效率。与目前发表的大多数方法不同,本文将数据中心视为电力市场中的消费者。我们的目的是使数据中心对电力市场条件的响应能力更强,同时对其性能的影响最小。在电力市场中,需求响应(DR)是一种通过鼓励消费者在价格峰值或网络压力期间调整其需求来提高电网效率的方法。通过实施涉及大量消费者的DR计划,可以潜在地节省大量的消耗和成本。传统上,灾难恢复在很大程度上是一个人工过程,然而,由于智能电网技术的部署,自动化灾难恢复正变得越来越普遍。在本文中,我们将数据中心中的服务器集群视为参与DR活动的能源消费者。我们给出了两种算法,使集群能够自动调整活动服务器的数量以响应DR请求,同时保持可接受的系统性能。我们使用真实轨迹来评估我们的算法。
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