CSR:Medium:Collaborative Research: Stochastically Robust Resource Allocation for Computing

Stochemistry Robust Resource Allocation for Computing该奖项由2009年美国复苏和再投资法案（公法111-5）资助。并行、分布式和基于Internet的计算、通信和信息系统是机器和网络的异构混合体。由于不确定性，如意外的机器故障，系统工作负载的变化或系统参数的不准确估计，它们经常会遇到性能下降。系统性能对不确定性具有鲁棒性是很重要的。这对计算机系统意味着什么？robust？？如何描述鲁棒性？如何确定一个鲁棒性的声明是真的，还是一个系统会失败？如何判断两个系统中哪一个更强大？这些是我们在这个项目中解决的问题类型，我们的团队包括来自科罗拉多州立大学和科罗拉多大学的教师、研究生和本科生，以及工业界的同事（DigitalGlobe）和国家实验室（NCAR，国家大气研究中心）。我们正在设计模型，指标，数学和算法工具，以及用于（1）导出鲁棒的系统资源管理方案和（2）量化满足给定不确定性的性能要求的概率的策略。我们正在通过与DigitalGlobe和NCAR合作来验证我们的研究，DigitalGlobe为谷歌地图和微软虚拟地球提供图像，NCAR的研究活动包括预测严重和灾难性天气。正在制定的健全概念具有广泛的适用性，将大大有助于满足各国建立和维持健全的信息技术基础设施的需要。

Stochastically Robust Resource Allocation for ComputingThis award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).Parallel, distributed, and Internet-based computing, communication, and information systems are heterogeneous mixtures of machines and networks. They frequently experience degraded performance due to uncertainties, such as unexpected machine failures, changes in system workload, or inaccurate estimates of system parameters. It is important for system performance to be robust against uncertainties.What does it mean for a computer system to be ?robust?? How can robustness be described? How does one determine if a claim of robustness is true, or if a system will fail? How can one decide which of two systems is more robust? These are the types of issues we address in this project, with our team of faculty, graduate students, and undergraduate students from Colorado State University and the University of Colorado, and colleagues in industry (DigitalGlobe) and a national laboratory (NCAR, National Center for Atmospheric Research).We are designing models, metrics, mathematical and algorithmic tools, and strategies for (1) deriving system resource management schemes that are robust, and (2) quantifying the probability of meeting performance requirements given uncertainties. We are validating our research by working with DigitalGlobe, which supplies images to Google Maps and Microsoft Virtual Earth, and NCAR, whose research activities include the prediction of severe and catastrophic weather. The robustness concepts being developed have broad applicability, and will significantly contribute to meeting national needs to build and maintain robust information technology infrastructures.