CAREER: Network Resilience: Theories, Algorithms, and Applications

网络是相互依赖和动态的组件的集合，这些组件组成了许多不同规模的关键系统，如社会系统、食品供应链和我们大脑中的神经网络。但是，这些网络很容易出现故障。一个微小的干扰可能会使整个网络越过一个临界点，并突然不可逆转地将其转变为不受欢迎的状态，导致大规模的灾难性崩溃。例如，生态网络的大规模灭绝，电网的连锁故障，以及人类和动物网络的社会习俗变化。弹性是指网络系统在面对内部干扰和环境变化时调整其活动以保留基本功能和避免大幅转移的能力。韧性丧失的代价有时是难以承受的：截至2021年1月25日，新冠肺炎大流行的爆发已在全球造成200多万人死亡，并继续导致越来越多的人死亡，越来越多的经济活动关闭。该奖项旨在为来自不同领域的系统，如生物学、生态学、交通运输等，为复杂网络系统的弹性奠定普遍的理论和实践基础。该奖项将设计快速而准确的算法来预测系统的弹性，即使只有部分信息已知，提供防止生态、生物或经济系统崩溃的方法，并指导对内部故障和环境变化具有弹性的技术系统的设计。包括K-12在内的学生将通过多种方式学习网络和弹性，从研究机会到讲座和网络攻击游戏设计，防御者的目标是创建一个弹性网络，资源有限，以抵御攻击者的战略破坏。该项目的技术目标分为三个方面。第一个推力创建了一个统一的理论，通过放松一些假设并认识到动态组件之间和相互作用系统之间的不同类型的相互作用，来捕捉不同系统的普遍弹性行为。第二个推力设计了快速而准确的算法，用于在拓扑或动力学信息不完全的情况下预测系统的弹性。最后一个推力开发了通过拓扑自适应和基于状态的控制来增强弹性的数学工具，以表征其在运行轨迹和整个恢复过程中的准备状态，从而实现可持续、可恢复和弹性的系统设计。这三项研究进展将通过对进展的全面评估来验证，包括计算机模拟和真实世界实验。这项研究工作将为网络弹性奠定基础，使其能够以足够的一般性进行预测和控制，以便将其应用于许多对不利扰动的弹性至关重要的领域。这一职业项目实现了当前对网络弹性理解方式的转变，产生了革命性的想法，以增强如何最好地构建和管理网络系统(人工系统)或自组织和适应(自然系统)，以增强其对内部故障和外部环境变化的弹性。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Networks are collections of interdependent and dynamic components that make up many crucial systems of various scales, such as the social systems, food supply chains, and the neural networks in our brain. However, these networks can be highly vulnerable to failures. A small disturbance may bring the whole network across a tipping point and shift it abruptly and irreversibly to an undesired state, resulting in large catastrophic collapses. Examples are mass extinctions in ecological networks, cascading failures in power grids, and social convention changes in human and animal networks. Resilience is the ability of networked systems to adjust their activity to retain basic functionality and avoid large shifts in the face of internal disturbances and environmental changes. The cost of resilience loss sometimes is unaffordable: The outbreak of the COVID-19 pandemic has caused over two million deaths worldwide as of January 25, 2021, and continues to kill increasingly more people and shut down increasingly more economic activities. This award aims to develop a universal theoretical and practical foundation for the resilience of complex networked systems, for systems from different fields, such as biology, ecology, transportation, and many more. This award will design fast and accurate algorithms to predict a system's resilience even when only partial information is known, offering ways to prevent the collapse of ecological, biological, or economic systems and guide the design of technological systems resilient to both internal failures and environmental changes. Students, including K-12, will be engaged in learning about networks and resilience in multiple ways, ranging from research opportunities to lectures and a cyber-attack game design, where the defender aims to create a resilient network with limited recourses to withstand the attacker's strategic damages.The technical aims of the project are divided into three thrusts. The first thrust creates a unified theory that captures a universal resilience behavior of different systems by relaxing some assumptions and recognizing different types of interactions between the dynamical components and among interacting systems. The second thrust designs fast and accurate algorithms for predicting systems' resilience with incomplete information on the topology or dynamics. The last thrust develops mathematical tools for resilience enhancement through topology adaptation and state-based control to characterize their readiness during the operation trajectory and throughout the recovery process, enabling sustainable, recoverable, and resilient system design. These three research thrusts will be validated by a comprehensive evaluation of the progress, including computer simulations and real-world experiments. This research effort will produce the foundation for network resilience that allows prediction and controlling it with sufficient generality to apply it to many areas where resilience to adverse perturbations is of paramount concern. This CAREER project enables a paradigm shift in how network resilience is currently understood, yielding transformative ideas to enhance how networked systems can best be built and managed (human-made systems) or self-organized and adapted (natural systems) to enhance their resilience to internal failures and external environmental changes.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.