EAGER: A Framework for joint optimization of power management and performance in virtualized, heterogeneous cloud computing environments

EAGER：虚拟化异构云计算环境中电源管理和性能联合优化的框架

• 批准号: 1253218
• 负责人: Kirk Pruhs
• 金额: $ 18.8万
• 依托单位: University of Pittsburgh
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-01 至 2015-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1253218&HistoricalAwards=false
• 关键词: EAGER; Framework; joint; optimization; power

The main objective of the proposed research project is to develop holistic approaches to the design of power optimization strategies for heterogeneous cloud computing environment. The focus will be on exploring the tradeoffs among the cloud computing physical infrastructure, including power-managed servers and cooling technology, virtualized infrastructure, and the middleware and service infrastructure. Contrary to cross-layer designs for energy optimization, where solutions are obtained through piecemeal approaches, the layered architecture is used to cast cloud computing energy optimization as an extended monotropic programming problem and derive a systematic analysis and design of global energy optimization strategies, whereby energy policy at a given layer uses subsets of the decision variables to achieve individual optimality and reduce the impact of carbon footprint on the environment. The research project provides a unique opportunity for graduate and undergraduate students to gain deep understanding of the basic science and engineering design principles of cloud computing and energy consumption in data centers. The outreach plan builds on existing minority and under-represented programs at the University of Pittsburgh to recruit and retain a diverse population of undergraduate and graduate students, and also seeks to establish collaborations with industrial institutions to leverage their educational programs and cloud infrastructure to advance the research project agenda.

拟议的研究项目的主要目标是开发整体的方法来设计的异构云计算环境的电源优化策略。重点将是探索云计算物理基础设施之间的权衡，包括电源管理服务器和冷却技术、虚拟化基础设施以及中间件和服务基础设施。与用于能量优化的跨层设计相反，在跨层设计中，解决方案是通过逐段的方法获得的，分层架构用于将云计算能量优化铸造为扩展的单变量编程问题，并导出全局能量优化策略的系统分析和设计，由此，给定层的能源政策使用决策变量的子集来实现个体最优，并减少碳足迹对能源的影响。环境保护该研究项目为研究生和本科生提供了一个独特的机会，以深入了解云计算和数据中心能耗的基本科学和工程设计原则。外展计划建立在匹兹堡大学现有的少数民族和代表性不足的项目的基础上，以招募和留住多样化的本科生和研究生，并寻求与工业机构建立合作，利用他们的教育计划和云基础设施来推进研究项目议程。