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

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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.