Dynamics of Complex Networks

复杂网络的动力学

• 批准号: 9988674
• 负责人: Albert-Laszlo Barabasi
• 金额: $ 17.2万
• 依托单位: University of Notre Dame
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-08-01 至 2004-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9988674&HistoricalAwards=false
• 关键词: Dynamics; Complex; Networks

9988674BarabasiIn many systems in Nature constituents form a highly interconnected network, offering a level of complexity that makes them practically untreatable with traditional methods. Examples include the metabolic network in a cell, social networks, business networks, the world wide web or the Internet. The inability of contemporary science to describe these systems currently limits advances in many disciplines, ranging from molecular biology to computer science. The objective of the present proposal is to capitalize on the increasing availability of topological information on real networks to uncover the basic mechanisms that determine the network topology. Our exploration is driven by the conviction that the emergence and the evolution of complex networks are governed by generic mechanisms that are common to many systems. To achieve our goal we propose a research program composed of three steps. First we plan to identify quantities that uniquely characterize the network topology, aiming to develop a set of measures, that eventually will allow us to construct a network with unique topological properties. Second, we plan to investigate the concept of universality: what are the mechanisms that determine the scaling exponents and the topology of the network. Third, we plan to study to which degree can a network be reconstructed from partial topological information.

9988674 barabasin在自然界的许多系统中，组成部分形成了一个高度互联的网络，其复杂性使得传统方法几乎无法对其进行处理。例子包括细胞中的代谢网络、社会网络、商业网络、万维网或互联网。当代科学无法描述这些系统，限制了从分子生物学到计算机科学等许多学科的进步。本提案的目的是利用真实网络中拓扑信息的日益增加的可用性来揭示决定网络拓扑的基本机制。我们的探索是由一种信念驱动的，即复杂网络的出现和演变是由许多系统共同的通用机制控制的。为了实现我们的目标，我们提出了一个由三个步骤组成的研究计划。首先，我们计划确定表征网络拓扑的唯一数量，旨在开发一套措施，最终将使我们能够构建具有独特拓扑属性的网络。其次，我们计划研究普适性的概念：决定缩放指数和网络拓扑结构的机制是什么。第三，我们计划研究在多大程度上可以从部分拓扑信息重构网络。