NetSE: Small: Multi-Resolution Analysis of Network Matrices

NetSE：小型：网络矩阵的多分辨率分析

• 批准号: 0916309
• 负责人: Yin Zhang
• 金额: $ 50万
• 依托单位: University of Texas at Austin
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2013-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0916309&HistoricalAwards=false
• 关键词: NetSE; Small; Multi; Resolution; Analysis

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5). Network matrices, such as traffic matrices, delay matrices, adjacency matrices, and social proximity matrices, are essential inputs to a wide range of network applications. Network matrices and the underlying network often exhibit a multi-faceted scaling behavior. To capture such multi-scale behavior, a particularly promising approach is Multi-Resolution Analysis (MRA), which creates multiple approximate representations of network matrix at different resolutions. This project will (i) develop a novel framework to enable network-centric MRA of network matrices, and (ii) use the framework to develop novel solutions to several network management tasks: missing value inference, design of experiments, traffic synthesis, and anomaly detection.Intellectual Merit: The project is multi-disciplinary by nature and will foster effective synergy between networking, statistics, data mining, and scientific computing. The MRA framework and its applications will deepen the understanding of the spatial and temporal characteristics of network matrices at different scales, and advance the state of art in several significant network management tasks.Broader Impact: The MRA framework is valuable to multiple scientific fields. The project is expected to produce publications in leading conferences and journals, and software that will be publicly available online. Through technology transfer, the network management solutions can potentially improve the operations of real ISP networks. The project will provide several graduate students' thesis research and honors undergraduate research projects. The research results will also be integrated into undergraduate and graduate curricula as well as outreach activities.

该奖项是根据2009年美国复苏和再投资法案（公法111-5）资助的。 网络矩阵，如流量矩阵、延迟矩阵、邻接矩阵和社会邻近矩阵，是各种网络应用的重要输入。 网络矩阵和底层网络通常表现出多方面的缩放行为。 为了捕捉这种多尺度行为，一种特别有前途的方法是多分辨率分析（MRA），它在不同的分辨率下创建网络矩阵的多个近似表示。 该项目将（i）开发一个新的框架，使网络矩阵的网络为中心的MRA，和（ii）使用该框架开发新的解决方案，以几个网络管理任务：缺失值推理，实验设计，流量合成，和异常检测。智力优点：该项目是多学科的性质，并将促进网络，统计，数据挖掘和科学计算之间的有效协同作用。 MRA框架及其应用将加深对不同尺度下网络矩阵的时空特征的理解，并在几个重要的网络管理任务中推进最新技术水平。更广泛的影响：MRA框架对多个科学领域都有价值。 预计该项目将在主要会议和期刊上发表出版物，并将在网上公开提供软件。 通过技术转让，网络管理解决方案可以潜在地改善真实的ISP网络的运营。该项目将提供几个研究生的论文研究和荣誉本科生的研究项目。研究成果还将纳入本科生和研究生课程以及外联活动。