CSR: Small: Collaborative Research: Software Defined Energy Adaptation in Large Scale Data Centers

CSR：小型：协作研究：大型数据中心的软件定义能源适应

• 批准号: 1421913
• 负责人: David Du
• 金额: $ 25万
• 依托单位: University of Minnesota-Twin Cities
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-10-01 至 2018-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1421913&HistoricalAwards=false
• 关键词: CSR; Small; Collaborative; Research; Software

Today many compute and data intensive applications are running on the computers in data centers. Therefore, data centers consume large amounts of energy. Within a data center, many compute, storage and networking components are coordinated together to support these applications. This project studies how to efficiently allocate resources in data centers to satisfy the requirements of these applications with guaranteed quality of service (QoS) and at the same time taking advantage of the available renewable (green) energy to reduce the total energy to be consumed. As the data centers increase in size and complexity, it is becoming clear that the traditional distributed control of their resources poses daunting problems in ensuring the desired agility and QoS support demanded by the enterprise applications. This problem is further compounded by the need for aggressive energy management in order to minimize energy cost, cope with power and thermal related constraints, and adapt to variability in the energy produced from local "green" sources. A distributed management of energy is particularly difficult since energy by its nature is a central resource that must be properly divided up among various infrastructure components in order to yield acceptable application performance. This project explores a flexible, policy driven, software defined mechanism to manage energy at all levels of the data center and for all major resources including networks, storage systems, and compute servers. A crucial aspect in this research is the coordination of energy management decisions at various levels which is essential to achieve optimal performance under given energy/thermal constraints. The project brings in the emerging concept of software defined resource management to seamlessly tackle the energy sustainability and corresponding QoS issues in data centers. The project also forms a pilot realization of the software defined data center, since energy adaptation requires an adept management of all major data center resources. A set of new algorithms in resource allocation, resource monitoring, QoS enforcement, energy allocation and distribution will be designed and developed. These algorithms will be implemented into a specific framework to demonstrate and validate the usage and benefits of the research. The broader impacts of the project include mechanisms to enhance energy sustainability of data centers and a comprehensive mechanism for software control of large computing systems. The project also augments the research being done in the NSF Industry/University Cooperative Research Center (IUCRC) on intelligent storage and will use it as a conduit for industry adoption of this research.

如今，许多计算和数据密集型应用程序都在数据中心的计算机上运行。因此，数据中心消耗大量的能源。在数据中心内，许多计算、存储和网络组件协调在一起以支持这些应用程序。该项目研究如何有效地分配数据中心的资源，以满足这些应用程序的要求，同时保证服务质量（QoS），同时利用可用的可再生（绿色）能源来减少总能源消耗。随着数据中心规模和复杂性的增加，越来越明显的是，传统的分布式资源控制在确保企业应用程序所需的敏捷性和 QoS 支持方面带来了令人畏惧的问题。由于需要积极的能源管理以最大限度地降低能源成本、应对电力和热力相关限制并适应当地“绿色”能源产生的能源的变化，这一问题进一步复杂化。 能源的分布式管理特别困难，因为能源本质上是一种中心资源，必须在各种基础设施组件之间适当划分，才能产生可​​接受的应用性能。 该项目探索了一种灵活的、策略驱动的、软件定义的机制，用于管理数据中心各个级别以及所有主要资源（包括网络、存储系统和计算服务器）的能源。这项研究的一个重要方面是各级能源管理决策的协调，这对于在给定的能源/热约束下实现最佳性能至关重要。 该项目引入了软件定义资源管理的新兴概念，以无缝解决数据中心的能源可持续性和相应的服务质量问题。该项目还形成了软件定义数据中心的试点实现，因为能源适应需要对所有主要数据中心资源进行熟练管理。将设计和开发一套在资源分配、资源监控、QoS实施、能量分配和分配方面的新算法。这些算法将被实施到特定的框架中，以展示和验证研究的用途和好处。 该项目更广泛的影响包括增强数据中心能源可持续性的机制以及大型计算系统软件控制的综合机制。该项目还增强了 NSF 行业/大学合作研究中心 (IUCRC) 正在进行的智能存储研究，并将其作为行业采用该研究的渠道。