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.

对复杂系统缺乏预测能力，无论是人类设计的还是自然进化的，都是当代科学的一个基本问题。互联网提供了一个典型的例子：它的架构和设计中没有任何东西可以解释它复杂的大规模结构。自然界中的许多复杂网络都具有互联网的这种特殊结构特征，但它们也表现出惊人的行为：它们在没有任何可观察到的路由通信协议的情况下有效地路由信息。因此，本研究课题的主要目的是探索复杂网络的结构与通信功能之间的关系，由加州大学圣地亚哥分校互联网数据分析合作协会（CAIDA）的计算机科学家和西班牙巴塞罗那大学的物理学家组成了一个国际研究小组。该项目包括理论建模和计算机模拟，以发现如果互联网30岁的域间拓扑结构已经自然地朝着一个结构，其中自然具有上级路由technology.The智力价值的这个项目是在利用这种自然的路由技术无限可扩展的互联网路由与最小的通信开销。如果成功，这个项目将解决一个长期存在的理论问题，即在复杂网络中构建一个最有效的路由算法。这些结果可能有助于消除现有互联网路由架构中严重的扩展限制，更广泛的影响是提高我们对大规模复杂网络的组织、功能和演化的基本原理的认识，改变如何建模、预测和控制它们的研究。网络结构和功能之间的基本联系的阐明对许多复杂系统的研究产生了深远的影响，包括搜索引擎，推荐和声誉系统，恐怖分子网络建模，癌症和大脑研究，蛋白质折叠和药物设计。