CSR: Small: Workload Shaping for Capacity and Power Provisioning in Storage Data Centers

为存储数据中心的容量和电源配置塑造工作负载摘要该奖项是根据2009年《美国复苏和再投资法案》(Public Law 111-5)资助的。托管服务和数据共享的迅猛增长推动了涵盖整个数据中心或整体数据中心的新一代存储虚拟化技术。准确的动态资源配置是实现这些服务中心经济高效且对环境敏感的运营的关键，目的是(I)减少占地面积、服务器硬件以及配电和冷却基础设施的固定成本，(Ii)降低管理和电力的运营成本，以及(Iii)减少过度使用能源带来的隐藏的环境和社会成本。本项目的目标是使用新的工作负载整形技术为存储服务器开发有效的动态资源配置和调度方案，以改善成本和能源消耗。该研究涉及具有优越性能特征的工作负载整形新算法的设计、分析、实现和性能评估。这将显著改善资源调配、容量预测和准入控制，以及能源和电力消耗。与传统的服务器调度技术不同，传统的服务器调度技术中，工作负载突发的负面影响甚至会影响到工作负载的正常运行部分，所提出的工作负载整形方法通过在线工作负载分解和重组来隔离突发负载并将其影响限制在局部区域。该项目将支持新兴信息技术部门的研究生教育，并将让本科生参与相关技术领域的研究。

Workload Shaping for Capacity and Power Provisioning in Storage Data CentersAbstractThis award is funded under the American Recovery and ReinvestmentAct of 2009 (Public Law 111-5).Tremendous growth in hosted services and data sharing are motivating a new generation of storage virtualization technologies that encompass the entire data center or ensembles of data centers. Accurate dynamic resource provisioning is critical to achieving cost-effective and environmentally-sensitive operation of these service centers in order to (i) reduce fixed costs for floor space, server hardware, and infrastructure for power distribution and cooling, (ii) lower the operational costs for management and electricity, and (iii) mitigate the hidden environmental and social costs of excessive energy use.The goals of this project are to develop effective dynamic resource provisioning and scheduling schemes for storage servers using novel workload shaping techniques to improve cost and energy consumption. The research involves the design, analysis, implementation, and performance evaluation of new algorithms for workload shaping with superior performance characteristics. This will result in significant improvements in resource provisioning, capacity prediction, and admission control, as well as energy and power consumption. Unlike traditional server scheduling techniques in which the negative effects of workload bursts affect even well-behaved portions of the workload, the proposed workload shaping approach isolates the bursts and confines their effects to localized regions using online workload decomposition and recombination.The project will support the education of graduate students in an emerging sector of Information Technology, and will also involve undergraduate engineering students in research in a topical technical area.