CSR: Small: Understanding and Modeling the Trade-Offs in Data Centers for Next-Generation Sustainable Management

CSR：小：理解和建模数据中心的权衡以实现下一代可持续管理

• 批准号: 1218505
• 负责人: Sandeep Gupta
• 金额: $ 45万
• 依托单位: Arizona State University
• 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: 2012-08-01 至 2017-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1218505&HistoricalAwards=false
• 关键词: CSR; Small; Understanding; Modeling; Trade

The success of cloud computing as a business model has led to several commercial cloud services for storage, data mining and searching, and multimedia content delivery. As cloud services penetrate emerging markets -- notably the smart-phone market -- conventional utility services such as television are becoming ?cloudized.? As the economy becomes more dependent on the efficient operation of cloud data centers (DCs), there?s an increasingly urgent need to design ?green? and energy-adaptive management software that optimizes the operation of a geographically distributed set of data centers under varying workload and energy conditions.Cyber-physical, proactive and predictive decision making is essential for a DC operating system that efficiently predicts, e.g., the workload and the power consumption when running multiple jobs on the same server and makes decisions, e.g., for redistributing the servicing virtual machines among varying number of available DCs, electricity cost, percentage of renewable energy supply and capacity of energy storage. This project is addressing the scientific and engineering challenges involved in decision making of such DC management arising from an array of complicating factors -- e.g., server heterogeneity, cyber-physical interactions between DCs and their environment, varying workload and electricity pricing -- and trade-offs -- e.g., energy-delay, time-accuracy, and cooling-computing . The project is developing a Green cyber-physical Data Center Simulator, GDCSim, for studying the tradeoffs in practical scenarios with several complicating factors. Project aims to enable a more sustainable cloud computing and to train engineers for a greener economy. The project findings are available through ASU-IMPACT lab?s website (http://impact.asu.edu/).

云计算作为一种商业模式的成功导致了一些用于存储、数据挖掘和搜索以及多媒体内容交付的商业云服务。随着云服务渗透到新兴市场（尤其是智能手机市场），电视等传统公用事业服务正变得“云化”。随着经济越来越依赖于云数据中心（dc）的高效运行，还有什么？越来越迫切的需要设计？绿色？能源适应性管理软件，在不同的工作负荷和能源条件下，优化地理分布的数据中心的运行。网络物理、前瞻性和预测性决策对于数据中心操作系统至关重要，数据中心操作系统可以有效地预测，例如，在同一台服务器上运行多个作业时的工作负载和功耗，并做出决策，例如，在不同数量的可用数据中心之间重新分配服务虚拟机、电力成本、可再生能源供应百分比和能量存储容量。该项目旨在解决数据中心管理决策中涉及的科学和工程挑战，这些挑战来自一系列复杂因素——例如，服务器异构性、数据中心与其环境之间的网络物理交互、不同的工作量和电价——以及权衡——例如，能源延迟、时间准确性和冷却计算。该项目正在开发绿色网络物理数据中心模拟器GDCSim，用于研究具有几个复杂因素的实际场景中的权衡。该项目旨在实现更可持续的云计算，并为绿色经济培训工程师。项目结果可通过亚利桑那州立大学impact实验室获得。网站（http://impact.asu.edu/）。