ITR-(NHS+ASE)-(Sim): Self-Organization of Complex Network Dynamics for Efficiency and Robustness

该奖项是根据在信息技术研究征集NSF-04-012项下提交给材料研究部的一份提案而颁发的。该奖项所涵盖的研究活动属于国家重点领域“科学与工程进展”和技术重点领域“计算建模或研究中的模拟创新”。该奖项支持网络动力学特性的计算研究。许多自然和人造系统都被构建成复杂的网络。例子包括基础设施网络，如电网、电话线和互联网，交通网络，如高速公路、铁路和航空公司，以及社会网络，如那些描述熟人、合作和恐怖分子的网络。其他复杂网络描述了工程学和生物学中的动态自适应控制系统。所有这些网络都由节点组成，在这些节点中，连接或交互由链接网状结构来描述。一般情况下，节点的行为是不同的，并且链路具有不同的强度或容量。通常，链路在节点之间传输一些量，包括信息、电力、材料、疾病或影响。因此，网络经常演进或构建，以确保传输对网络本身的变化或其环境或任务的变化是有效和健壮的。在许多自然网络中，以及在一些设计的网络中，进化或组织以变得高效和健壮的能力内置在网络本身的动态中。了解和控制复杂网络的演化动力学对国家和国土安全以及先进的科学和工程都具有重要意义。现有的大多数网络研究主要关注其结构性质。相反，这项研究将探索网络的动态如何自组织以确保高效和稳健的行为。它还将研究网络的动态如何与其结构的演变相关。我们的目标是描述和了解如何设计网络动态来以强健的方式优化和控制他们的行为。另一个目标将是相反的，即了解如何禁用网络行为。具体地说，这项工作将以最近的成果为基础，这些成果探讨了无标度网络中运输的效率、社会网络中出现的无标度领导结构和集体效率，以及适应性控制网络中渠化的演变，这是一种已知在发育生物学中很重要的稳健性。旨在捕捉真实世界网络基本潜在行为的简单动态网络模型将使用统计物理的工具和方法进行研究，包括大规模计算机模拟。然后将研究结果与真实世界的网络进行比较。研究结果将对国家和国土安全具有重要意义，因为它们将帮助我们了解如何设计和建立高效可靠的基础设施和交通网络，以及如何通过利用网络动态的脆弱性来扰乱恐怖分子或疾病活动。研究结果还将提高我们对网络上自适应控制系统的理解和设计，从而促进科学和工程的发展。研究生将参与这个项目。PI还承诺让代表不足的群体参与进来。%

This award was made on a proposal submitted to the Division of Materials Research under the Information Technology Research solicitation NSF-04-012. Research activities covered by this award fall under the National Priority Area, "Advances in Science and Engineering," and the Technical Focus Area, "Innovation in Computational Modeling or Simulation in Research." This award supports computational research in the dynamical properties of networks. Many natural and man-made systems are structured as complex networks. Examples include infrastructure networks, such as the power-grid, phone lines, and the Internet, transportation networks, such as highways, railways, and airways, and social networks, such as those describing acquaintanceships, collaborations, and terrorists. Other complex networks describe dynamic adaptive control systems in both engineering and biology. All of these networks consist of nodes where connections or interactions are described by a mesh of links. Generally, the nodes will behave heterogeneously, and the links will have different strengths or capacities. Typically, the links transport some quantity, including information, power, material, disease, or influence, between the nodes. Therefore, the networks often evolve, or are constructed, to ensure that the transport is efficient and robust to changes in either the network itself or to changes in its environment or task. In many natural networks, and in some designed networks, the capacity to evolve or organize to become efficient and robust is built into the dynamics of the network itself. Understanding and controlling the evolutionary dynamics of complex networks is important to both national and homeland security and to advanced science and engineering.Most existing studies of networks are concerned primarily with their structural properties. This research will, instead, explore how the dynamics of networks can self-organize to ensure efficient and robust behavior. It will also examine how the dynamics of networks is related to the evolution of their structure. The goal will be to characterize and understand how network dynamics can be designed to optimize and control their behavior in a robust way. Another goal will be the opposite, namely to understand how the behavior of a network can be disabled. Specifically, the work will build upon recent results that have explored the efficiency of transport in scale-free networks, the emergence of scale-free leadership structure and of collective efficiency in social networks, and the evolution of canalization, a type of robustness known to be important in developmental biology, in adaptive control networks. Simple models of dynamic networks that aim to capture the essential underlying behavior of real-world networks will be studied with the tools and methods of statistical physics, including large-scale computer simulations. The results will then be compared with real-world networks.The results of the research will be important to national and homeland security because they will help us understand how to design and build efficient and reliable infrastructure and transportation networks, and how terrorist or disease activity may be disrupted by exploiting the vulnerabilities of the network dynamics. The results will also advance science and engineering by improving our understanding and design of adaptive control systems on networks.Graduate students will be involved with this project. The PI also has a commitment to involvement of underrepresented groups.%%%