CRISP Type 2: Collaborative Research: Towards Resilient Smart Cities

CRISP 类型 2：协作研究：迈向弹性智能城市

• 批准号: 1541108
• 负责人: Arif Sarwat
• 金额: $ 50万
• 依托单位: Florida International University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1541108&HistoricalAwards=false
• 关键词: CRISP; Type; Collaborative; Research; Towards

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.

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将智能交通、无线系统、供水网络和电网等网络物理关键基础设施(CI)协同集成到统一的智能城市中。这种智能城市配置项具有很大的资源依赖性，因为它们共享能源、计算、无线频谱、用户和人员以及经济投资，因此容易因日常运营、自然灾害或恶意攻击而发生相关故障。保护未来的智能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。这样的流程必须能够自适应和优化地重新分配智慧城市资源，以从失败中恢复。这个关键的弹性相互依赖的基础设施系统和流程(CRISP)协作研究项目的目标是通过依赖于机器学习、运筹学、行为经济学和认知心理学的协调和跨学科的方法来应对这一根本挑战，为弹性智能城市奠定数学基础。预期结果将在理解多个网络物理基础设施和弹性资源管理之间的协同效应方面开辟新的天地，从而促进智能城市的全球部署。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。该项目将有来自工程学、计算机科学、经济学和心理学的不同背景的学生参加，他们将接受与智能城市和弹性相关的研究问题的培训。这项研究将引入一个基础性的、变革性的分析框架，利用城市的CI之间的协同作用，产生考虑到技术和人的因素的弹性资源管理方案。通过将来自跨学科领域的研究人员聚集在一起，该框架产生了几个进步：1)严格的数学工具，用于通过来自图论、幂指数、机器学习和随机空间模型的新工具的补充组合来描述CI之间的相互依赖；2)弹性资源管理机制，其从诸如行为博弈论等框架中提出概念，以使得能够在面临不同智力水平的代理的故障时对共享CI资源进行优化管理；3)行为模型，用于表征智能城市居民和CI之间的信任关系；4)行为研究，就如何以某种方式影响智能城市的用户，以提高智能城市的弹性提供指导；以及5)大型智能城市模拟器，结合实际实验，弥合理论和实践之间的差距。来自该项目的见解将应用于未来的科学网络基础设施，这些基础设施可能既相互联系又相互依存。模拟器将是一个软件制品，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。