CRISP Type 2: Collaborative Research: Towards Resilient Smart Cities

实现真正智慧城市的愿景是未来十年最紧迫的技术挑战之一。这一愿景的成功需要网络物理关键基础设施（ci）的协同集成，如智能交通、无线系统、供水网络和电网，形成一个统一的智能城市。这种智慧城市ci由于共享能源、计算、无线频谱、用户和人员、经济投资等资源依赖性强，容易因日常运营、自然灾害或恶意攻击而出现相关故障。保护未来的智慧城市免受此类故障的影响，需要在管理城市公共CI资源的过程中注入弹性。这些过程必须能够自适应地、最佳地重新分配智慧城市资源，以便从故障中恢复。关键弹性相互依赖基础设施系统和流程（CRISP）合作研究项目的目标是通过协调和跨学科的方法解决这一根本性挑战，该方法依赖于机器学习、运筹学、行为经济学和认知心理学，为弹性智慧城市奠定数学基础。预期结果将在理解多种网络物理基础设施和弹性资源管理之间的协同作用方面开辟新的领域，从而促进智慧城市的全球部署。这项研究将在弹性系统、网络物理系统、安全和隐私工程、博弈论、计算机和网络科学、行为经济学、数据分析和心理学等领域取得进展。该项目将涉及来自工程、计算机科学、经济学和心理学等不同背景的学生，他们将接受与智慧城市和弹性相关的相关研究问题的培训。该项目还将有助于促进居民与各种技术流程之间的信任，这些技术流程是智慧城市运营的基础。本研究将引入一个基础的、变革性的分析框架，以利用城市ci之间的协同作用，产生具有弹性的资源管理方案，同时认识到技术和人为因素。通过汇集跨学科领域的研究人员，该框架产生了以下几个进展：1)通过图论、幂指数、机器学习和随机空间模型等新工具的互补组合，通过严格的数学工具来描绘ci之间的相互依赖关系；2)弹性资源管理机制，它推进了行为博弈论等框架的概念，使共享CI资源在面对不同智能水平的代理所导致的故障时能够进行优化管理；3)表征智慧城市居民与ci信任关系的行为模型；4)行为研究，提供指引，说明如何以这种方式影响社区使用者，以改善社区的弹性；5)大型智慧城市模拟器与现实实验相结合，将弥合理论与实践之间的差距。这个项目的见解将应用于未来的科学网络基础设施，这些基础设施可能是相互联系的，也可能是相互依存的。该模拟器将是一个软件工件，将成为旨在理解（例如）智能城市的科学网络基础设施的有用组成部分。

Realizing the vision of truly smart cities is one of the most pressing technical challenges of the coming decade. The success of this vision requires synergistic integration of cyber-physical critical infrastructures (CIs) such as smart transportation, wireless systems, water networks, and power grids into a unified smart city. Such smart city CIs have significant resource dependence as they share energy, computation, wireless spectrum, users and personnel, and economic investments, and as such are prone to correlated failures due to day-to-day operations, natural disasters, or malicious attacks. Protecting tomorrow's smart cities from such failures requires instilling resiliency into the processes that manage the city's common CI resources. Such processes must be able to adaptively and optimally reallocate smart city resources to recover from failure. The goal of this Critical Resilient Interdependent Infrastructure Systems and Processes (CRISP) collaborative research project is to address this fundamental challenge via a coordinated and interdisciplinary approach that relies on machine learning, operations research, behavioral economics, and cognitive psychology to lay the mathematical foundations of resilient smart cities. The anticipated results will break new ground in the understanding of synergies between multiple cyber-physical infrastructure and resilient resource management thus catalyzing the global deployment of smart cities. This research will yield advances to the areas of resilient systems, cyber-physical systems, security and privacy engineering, game theory, computer and network science, behavioral economics, data analytics, and psychology. The project will involve students from diverse backgrounds across engineering, computer science, economics, and psychology that will be trained on pertinent research issues related to smart cities and resiliency. The project will also contribute to fostering trust between residents and the various technological processes that are fundamental to the operation of a smart city.This research will introduce a foundational, transformational, analytical framework for leveraging synergies between a city's CIs to yield resilient resource management schemes cognizant of both technological and human factors. By bringing together researchers from interdisciplinary fields, this framework yields several advances: 1) Rigorous mathematical tools for delineating the inter-dependencies between CIs via a complementary mix of novel tools from graph theory, power indices, machine learning, and random spatial models; 2) Resilient resource management mechanisms that advance notions from frameworks such as behavioral game theory to enable optimized management of shared CI resources in face of failures stemming from agents of varying intelligence levels; 3) Behavioral models for characterizing the trust relationships between the residents of a smart city and the CIs; 4) Behavioral studies that provides guidelines on how to influence the users of the CIs in such a way so as to improve the resiliency of the CIs; and 5) Large-scale smart city simulators coupled with realistic experiments that will bridge the gap between theory and practice. The insights from this project will apply to the future scientific cyber-infrastructures that are likely to be interconnected as well as interdependent. The simulator will be a software artifact that would be a useful component of a scientific cyberinfrastructure aimed at understanding (for example) smart cities.