Coordinate Systems for the Internet

互联网坐标系

• 批准号: 0322990
• 负责人: Mark Crovella
• 金额: $ 22.2万
• 依托单位: Trustees of Boston University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-08-15 至 2007-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0322990&HistoricalAwards=false
• 关键词: Coordinate; Systems; Internet

This project seeks to answer the questions of network proximity estimation, other than direct measurement, by exploring a new analysis approach, combined with large-scale network measurement. Currently, there are very few methods for estimating network proximity, which can add significant overhead to both application and network in terms of delays and additional traffic. Newly emerging Internet applications, e.g. content delivery networks, peer-to-peer networks, multiuser games, overlay routing networks, and applications employing dynamic server selection, depend for its optimal configuration on accurate measures of network proximity. Recent effort in network proximity estimation has suggested that a promising approach may be to model network distances using coordinate systems; that is, via an embedding of network distances into Euclidean space. This approach has many appealing properties, but many fundamental questions remain unanswered: Is a Euclidean embedding effective in general? What is the appropriate dimension to use, and what is the best method for mapping distance measurements into a Euclidean space? How scalable are the resulting schemes? For what sorts of distance metrics are such schemes appropriate? The new analytic approaches proposed here are based on linear algebraic techniques, in particular the application of Principal Component Analysis to the problem of constructing good coordinate systems for the Internet. This project will collect and analyze a large set of network measurements to assess coordinate schemes on truly representative data and develop new algorithms for constructing coordinate schemes that are accurate and yet scalable to thousands of nodes, made available in the form of freely distributed tools.

该项目旨在通过探索一种新的分析方法与大规模网络测量相结合，以回答网络接近估计的问题，除非直接测量。当前，估计网络接近性的方法很少，这可以在延迟和其他流量方面为应用程序和网络增加大量的开销。新兴的互联网应用程序，例如内容交付网络，点对点网络，多源游戏，叠加路由网络以及采用动态服务器选择的应用程序，取决于其最佳配置，取决于网络接近的准确度量。网络接近性估计的最新努力表明，一种有希望的方法可能是使用坐标系建模网络距离。也就是说，通过将网络距离嵌入到欧几里得空间中。这种方法具有许多吸引人的财产，但是许多基本问题仍未得到解决：欧几里得嵌入一般有效吗？什么是适当的维度，将距离测量结果映射到欧几里得空间中的最佳方法是什么？产生的方案有多可扩展？对于哪种距离指标，此类方案适合使用？ 这里提出的新分析方法基于线性代数技术，特别是将主成分分析应用于为互联网构建良好坐标系的问题。该项目将收集和分析一系列网络测量值，以评估真正代表性数据的坐标方案，并开发新的算法，用于构建坐标方案，这些方案是准确但可扩展到数千个节点的，以自由分布的工具的形式提供。