CSR: Small: Energy Management for Heterogeneous MapReduce Data Centers

CSR：小型：异构 MapReduce 数据中心的能源管理

• 批准号: 1018467
• 负责人: Ying Lu
• 金额: $ 43.29万
• 依托单位: University of Nebraska-Lincoln
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-01 至 2014-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1018467&HistoricalAwards=false
• 关键词: CSR; Small; Energy; Management; Heterogeneous

Data-center-level energy management techniques have recently shown a lot of promise in improving data center energy efficiency. One challenge in developing such techniques is to support important types of workload. Current approaches, however, only consider managing compute-intensive applications. How to execute data-intensive parallel computations energy-efficiently remains a difficult open problem. World data is growing exponentially, doubling its size every three years. To facilitate large-scale data analysis and processing, a growing number of data centers start to support workloads that are managed with MapReduce-style frameworks. To support this increasingly popular workload energy-efficiently becomes very important.This project develops an energy management software system for heterogeneous MapReduce data centers. It is novel in several ways. First, it considers both computing energy and cooling energy and jointly minimizes their sum. Second, it develops feedback control algorithms to achieve energy-efficient utilization of multiple resources in heterogeneous data centers. Third, it develops aggressive consolidation techniques, matching the number of active nodes to the current needs of the workload. Novel consolidation-aware data management techniques are developed to make data placement and replication cooperative with server consolidation, saving energy while ensuring applications data availability and performance. If successful, this project will have significant impact on the society, by greatly conserving data center energy expenditures and corresponding carbon emissions footprint. Besides the technological impact, via outreach activities, curriculum development and matching minority students with this research, this project informs and educates the broader society and provides students hands-on experience in building energy-efficient computing systems.

数据中心级别的能源管理技术最近在提高数据中心能源效率方面显示出了很大的希望。开发此类技术的一个挑战是支持重要类型的工作负载。然而，目前的方法只考虑管理计算密集型应用程序。如何高效地执行数据密集型并行计算仍然是一个难题。世界数据呈指数级增长，每三年翻一番。为了便于大规模数据分析和处理，越来越多的数据中心开始支持使用mapreduce风格框架管理的工作负载。高效地支持这种日益流行的工作负载变得非常重要。本课题为异构MapReduce数据中心开发能源管理软件系统。它在几个方面都是新颖的。首先，它同时考虑计算能量和冷却能量，并使两者之和最小。其次，开发了反馈控制算法，实现异构数据中心中多种资源的高效利用。第三，它开发了积极的整合技术，使活动节点的数量与工作负载的当前需求相匹配。开发了新的支持整合的数据管理技术，使数据放置和复制与服务器整合协作，在确保应用程序数据可用性和性能的同时节省能源。如果成功，该项目将通过大大节省数据中心的能源支出和相应的碳排放足迹，对社会产生重大影响。除了科技上的影响外，透过外展活动、课程发展及将少数族裔学生与本研究配对，本计划向更广泛的社会提供资讯和教育，并为学生提供建造节能电脑系统的实践经验。