University - Industry Cooperative Research Programs in the Mathematical Sciences

数学科学产学合作研究项目

• 批准号: 9705109
• 负责人: Thomas Kurtz
• 金额: $ 7.1万
• 依托单位: University of Wisconsin-Madison
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1997
• 资助国家: 美国
• 起止时间: 1997-06-01 至 2000-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9705109&HistoricalAwards=false
• 关键词: University; Industry; Cooperative; Research; Programs

Enormous data sets are now available from high-quality traffic measurements for communications networks. Analysis of this data has revealed unexpected properties of traffic behavior which may critically affect network performance. Unfortunately, the development of statistical and mathematical techniques for efficiently dealing with this abundance of data and for effectively analyzing newly-observed phenomena has not kept up with the rate at which newer and larger data sets of traffic measurements are being captured, nor with the pace at which networks themselves change. The planned research program responds directly to the need for new approaches to network traffic and performance analysis in order to effectively exploit these large data sets and to understand the impact of the newly-observed phenomena. A postdoctoral research fellow will be appointed to work with researchers at the Information Sciences Research Center at AT&T Labs and the University of Wisconsin - Madison. The research associate will provide the primary link in the planned collaborative research program. This project is jointly supported by the MPS Office of Multidisciplinary Activities (OMA) and the Division of Mathematical Sciences (DMS)

现在可以从通信网络的高质量流量测量中获得海量数据集。对这些数据的分析揭示了流量行为的意外特性，这些特性可能会严重影响网络性能。不幸的是，用于有效处理这些大量数据和有效分析新观察到的现象的统计和数学技术的发展跟不上捕获更新的和更大的流量测量数据集的速度，也跟不上网络本身变化的速度。计划中的研究计划直接回应了对网络流量和性能分析的新方法的需求，以便有效地利用这些大型数据集，并了解新观察到的现象的影响。一名博士后研究员将被任命与AT&amp；T Labs信息科学研究中心和威斯康星大学麦迪逊分校的研究人员合作。研究助理将在计划中的合作研究计划中提供主要联系。该项目由公安部多学科活动办公室(OMA)和数学科学司(DMS)联合支持。