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CSR: Small: Scheduling Energy Consumption in Green Datacenters

CSR: Small: Scheduling Energy Consumption in Green Datacenters
CSR:小:安排绿色数据中心的能源消耗
批准号:
1117368
负责人:
Ricardo Bianchini
金额:
$42.0万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2011
资助国家:
美国
项目状态:
已结题
起止时间:
2011-09-01 至 2015-08-31

项目摘要

项目成果

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中文摘要
翻译
今天的巨大能源消耗?美国的数据中心意味着高昂的金钱和环境成本;后者是因为美国生产的大部分电力来自燃煤,这是一种温室气体密集型的能源生产方式。我们把这种能量称为棕能量。,而不是绿色的?清洁能源生产的能源。为了降低这两种成本,一种日益流行的方法是让数据中心自己生产绿色能源,或者直接从附近的绿色能源工厂获取电力。鉴于这一趋势,该项目的目标是研究如何最好地利用太阳能和风能来降低数据中心的能源成本和棕色能源消耗。使用这些类型的绿色能源的主要挑战是它们并不总是可用的。在此背景下,我们的研究重点是:(1)表征和建模数据中心工作负载和绿色能源生产;(2)设计负荷调度和能源使用政策;(3)设计考虑绿色能源的能源管理政策;(4)设计利用我们的模型和政策的系统。我们的项目将在许多方面影响社会,包括:(1)减少数据中心的棕色能源消耗和碳足迹;(二)促进绿色能源的生产和消费;(3)创造在数据中心开发绿色能源所需的机器,以获得最高效益。此外,我们认为,以如此清晰的方式开展工作,Ned的社会影响将帮助我们吸引和培养多样化和忠诚的本科生和研究生。
英文摘要
The massive energy consumption of today?s datacenters translates into high monetary and environmental costs; the latter because most of the electricity produced in the US comes from burning coal, a greenhouse-gas-intensive approach for producing energy. We refer to such energy as ?brown?, as opposed to the ?green? energy produced by clean energy sources.An increasingly popular approach for reducing both costs is for datacenters to generate their own green energy or draw power directly from a nearby green energy plant. In light of this trend, the goal of this project is to study how best to exploit solar and wind energy for lowering energy costs and brown energy consumption in datacenters. The major challenge in using these types of green energy is that they are not always available.In this context, our research focuses on: (1) Characterizing and modeling datacenter workloads and green energy production; (2) Designing load scheduling and energy usage policies; (3) Designing energy management policies that account for green energy; and (4) Designing systems that leverage our models and policies.Our project will impact society in many ways, including: (1) reducing the brown energy consumption and the carbon footprint of datacenters; (2) promoting the generation and consumption of green energy; and (3) creating the machinery needed to exploit green energy in datacenters for highest benefit. Furthermore, we believe that undertaking work with such clearly defined societal impact will help us attract and train a diverse and committed set of undergraduate and graduate students.
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