NetSE: Medium: Discovering Hyperbolic Metric Spaces Hidden beneath the Internet and Other Complex Networks

NetSE：中：发现隐藏在互联网和其他复杂网络之下的双曲度量空间

• 批准号: 1441828
• 负责人: Dmitri Krioukov
• 金额: $ 19.08万
• 依托单位: Northeastern University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-02-01 至 2016-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1441828&HistoricalAwards=false
• 关键词: NetSE; Medium; Discovering; Hyperbolic; Metric

The lack of predictive power over complex systems, either designed by humans or evolved by nature, is a foundational problem in contemporary science. The Internet offers a paradigmatic example:nothing in its architecture and design explains its complex large-scale structure. Many complex networks in nature share this peculiar structural character of the Internet, but they also manifest phenomenal behavior: they efficiently route information without any observable routing communication protocol. Hence, the main objective of this project is to explore the relationship between the structure and communication function of complex networks.An international team of researchers assembled for this project includes computer scientists from the Cooperative Association for Internet Data Analysis (CAIDA) at the University of California San Diego, and physicists from the University of Barcelona, Spain. The project includes theoretical modeling and computer simulations to discover if the Internet 30-year old interdomain topology has naturally evolved toward a structure for which nature has superior routing technology.The intellectual merit of this project is in the utilization of this natural routing technology for infinitely scalable Internet routing with minimal communication overhead. If successful, this project will solve a long-standing theoretical problem of constructing a maximally efficient algorithm for routing in complex networks. These results may help to remove serious scaling limitations within the existing Internet routing architecture.The broader impact is in improving our knowledge of the basic principles of organization, function, and evolution of large-scale complex networks, transforming research on how to model, predict, and control them. The elucidation of fundamental connections between network structure and function has far-reaching impact on the study of many complex systems, including search engines, recommender and reputation systems, terrorist network modeling, cancer and brain research, protein folding, and drug design.

缺乏对复杂系统的预测能力，无论是人类设计的还是自然发展的，是当代科学中的基本问题。 Internet提供了一个范式的例子：其体系结构和设计中的任何内容都没有解释其复杂的大规模结构。自然界中许多复杂的网络都具有互联网的独特结构特征，但它们也表现出了惊人的行为：它们有效地路由信息，而无需任何可观察到的路由通信协议。因此，该项目的主要目的是探索复杂网络的结构和通信功能之间的关系。为该项目组装的国际研究人员团队包括来自互联网数据分析合作协会（CAIDA）的计算机科学家加利福尼亚圣地亚哥和西班牙巴塞罗那大学的物理学家。该项目包括理论建模和计算机模拟，以发现30年历史的互联网拓扑是否自然发展朝着具有卓越的路由技术的结构。该项目的智力优点在于将这种自然路由技术用于无限地利用可扩展的Internet路由，并以最小的通信开销。如果成功的话，该项目将解决一个长期的理论问题，即构建一种在复杂网络中路由的最大有效算法。这些结果可能有助于消除现有的Internet路由体系结构内的严重规模限制。更广泛的影响在于我们对组织，功能和大规模复杂网络的基本原理的了解，从而改变有关如何建模，预测的研究并控制它们。网络结构与功能之间的基本联系阐明对许多复杂系统的研究，包括搜索引擎，推荐和声誉系统，恐怖网络建模，癌症和大脑研究，蛋白质折叠以及药物设计。