Resource Scheduling with QoS for Parallel I/O Systems

并行 I/O 系统的具有 QoS 的资源调度

• 批准号: 0541369
• 负责人: Peter Varman
• 金额: --
• 依托单位: William Marsh Rice University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-08-15 至 2012-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0541369&HistoricalAwards=false
• 关键词: Resource; Scheduling; QoS; Parallel; Systems

The architecture and usage modalities of storage systems have been revolutionized by advances in disk drive and networking technologies. Resource management issues occupy a central and increasingly important role in the operation of data centers that must coordinate the operation of large numbers of concurrent devices and serve hundreds of gigabytes of data per second. Such shared storage servers are being proposed as a cost-effective solution for maintaining data repositories. This research effort addresses resource allocation and scheduling issues that arise in multiplexing a shared storage server and seeks to provide isolation and performance guarantees for multiple contending flows that may have different characteristics. The research is developing robust models, algorithms, and mechanisms that enable efficient sharing of server I/O resources while enforcing performance guarantees, in the presence of dynamically varying resource constraints. The results will also have applicability to systems of heterogeneous servers. The intellectual advance pursued in this research is the systematic investigation of a new set of resource management issues that arise in the shared server environment. It studies, at a fundamental level, the problem of providing fair or differentiated quality of service among diverse concurrent clients (flows) accessing a shared parallel I/O system. The work is developing robust models that incorporate the unique resource constraints and performance responses arising in parallel I/O, developing efficient algorithms for adaptive resource allocation, formal characterization of the solutions with respect to performance and stability, and the development of simulation infrastructure for empirical evaluation of the solutions.The impact of the research will be more robust and scalable resource management for data centers such as commercial and supercomputing server environments. The research will produce mechanisms to enforce service agreements between the service provider and concurrent clients, reaping the economies of scale of shared resources and the increasing economic benefits of consolidated management. The research will also result in the training and education of graduate students in a growing sector of the information technology industry.

存储系统的体系结构和使用方式已经因磁盘驱动器和网络技术的进步而发生了革命性变化。资源管理问题在数据中心的运营中占据着越来越重要的中心地位，数据中心必须协调大量并发设备的操作，并每秒处理数百GB的数据。这种共享存储服务器被提议作为维持数据储存库的一种具有成本效益的解决办法。这项研究工作解决了资源分配和调度问题，出现在多路复用共享存储服务器，并寻求提供隔离和性能保证多个竞争流，可能具有不同的特点。该研究正在开发强大的模型，算法和机制，使服务器I/O资源的有效共享，同时执行性能保证，在动态变化的资源约束的存在。结果也将具有适用性的异构服务器的系统。在这项研究中追求的智力进步是一组新的资源管理问题，出现在共享服务器环境中的系统调查。它研究，在一个基本的水平上，提供公平的或不同的服务质量之间的并发客户端（流）访问一个共享的并行I/O系统的问题。这项工作是开发强大的模型，将独特的资源约束和并行I/O产生的性能响应，开发有效的算法，自适应资源分配，正式表征的解决方案方面的性能和稳定性，和模拟基础设施的开发，用于解决方案的实证评估。研究的影响将是数据中心的资源管理更加健壮和可扩展例如商业和超级计算服务器环境。 这项研究将产生机制，以执行服务提供商和并发客户端之间的服务协议，收获共享资源的规模经济和合并管理的经济效益不断增加。这项研究还将导致在信息技术产业的一个不断增长的部门的研究生的培训和教育。