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并结合大规模网络测量来回答直接测量之外的网络邻近度估计问题。目前，估计网络邻近度的方法很少，这会在延迟和额外流量方面给应用程序和网络增加显着的开销。新兴的互联网应用，例如内容交付网络、对等网络、多用户游戏、覆盖路由网络以及采用动态服务器选择的应用程序的最佳配置取决于对网络邻近度的准确测量。最近在网络邻近度估计方面的努力表明，一种有前途的方法可能是使用坐标系对网络距离进行建模；也就是说，通过将网络距离嵌入到欧几里德空间中。这种方法具有许多吸引人的特性，但许多基本问题仍未得到解答：欧几里得嵌入总体上有效吗？使用什么合适的维度？将距离测量映射到欧几里得空间的最佳方法是什么？由此产生的方案的可扩展性如何？这种方案适合什么样的距离度量？ 这里提出的新分析方法基于线性代数技术，特别是主成分分析在为互联网构建良好坐标系的问题上的应用。该项目将收集和分析大量网络测量结果，以评估真正具有代表性的数据的坐标方案，并开发新的算法来构建准确且可扩展至数千个节点的坐标方案，并以免费分发工具的形式提供。