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
基本信息
- 批准号:1541105
- 负责人:
- 金额:$ 110万
- 依托单位:
- 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 2021-09-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
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、水网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。此类智慧城市CI具有显著的资源依赖性,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,需要将弹性灌输到管理城市公共CI资源的流程中。这些过程必须能够自适应地和最佳地重新分配智慧城市资源,以从故障中恢复过来。这个关键弹性相互依赖基础设施系统和过程(CRISP)合作研究项目的目标是通过协调和跨学科的方法来解决这一根本挑战,该方法依赖于机器学习,运筹学,行为经济学和认知心理学,为弹性智能城市奠定数学基础。预期的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作用方面开辟新的天地,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智慧城市运行所必需的各种技术流程之间的信任。该研究将引入一个基础性的、转型性的分析框架,以利用城市CI之间的协同效应,产生既认识到技术因素又认识到人为因素的弹性资源管理方案。通过将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,用于通过图论,幂指数,机器学习和随机空间模型的新工具的互补组合来描绘CI之间的相互依赖关系;(二)灵活的资源管理机制,从行为博弈论等框架中提出概念,以实现共享CI的优化管理面对不同智能水平的代理所产生的故障时的资源; 3)用于表征智能城市居民与CI之间的信任关系的行为模型; 4)行为研究,提供如何影响CI用户的指导方针,以便提高CI的弹性; 5)大规模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。该项目的见解将适用于未来的科学网络基础设施,这些基础设施可能是相互关联和相互依赖的。模拟器将是一个软件工件,将是旨在理解(例如)智能城市的科学网络基础设施的有用组成部分。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Walid Saad其他文献
Joint User Grouping, Version Selection and Bandwidth Allocation for Live Video Multicasting
直播视频组播的联合用户分组、版本选择和带宽分配
- DOI:
10.1109/tcomm.2021.3115480 - 发表时间:
2021 - 期刊:
- 影响因子:8.3
- 作者:
Zhilong Zhang;Minyin Zeng;Danpu Liu;Walid Saad;Shuguang Cui;H. Vincent Poor - 通讯作者:
H. Vincent Poor
Sensing Aided Channel Estimation in Wideband Millimeter-Wave MIMO Systems
宽带毫米波 MIMO 系统中的传感辅助信道估计
- DOI:
10.1109/iccworkshops57953.2023.10283636 - 发表时间:
2023 - 期刊:
- 影响因子:0
- 作者:
Rakesh Mundlamuri;Rajeev Gangula;C. Thomas;F. Kaltenberger;Walid Saad - 通讯作者:
Walid Saad
Computer Vision-Based Localization With Visible Light Communications
基于计算机视觉的可见光通信定位
- DOI:
10.1109/twc.2021.3109146 - 发表时间:
2022-03 - 期刊:
- 影响因子:10.4
- 作者:
Lin Bai;Yang Yang;Mingzhe Chen;Chunyan Feng;Caili Guo;Walid Saad;Shuguang Cui - 通讯作者:
Shuguang Cui
Investigation of genes that may contribute to disease tropism in Leishmania species
研究可能有助于利什曼原虫物种向病性的基因
- DOI:
- 发表时间:
2007 - 期刊:
- 影响因子:0
- 作者:
Walid Saad - 通讯作者:
Walid Saad
Pilot Optimization and Channel Estimation Scheme for Semantic Communication: A Framework for Edge Intelligence
语义通信的导频优化和信道估计方案:边缘智能框架
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Kitae Kim;Y. Tun;Md. Shirajum Munir;Walid Saad;Choong Seon Hong - 通讯作者:
Choong Seon Hong
Walid Saad的其他文献
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{{ truncateString('Walid Saad', 18)}}的其他基金
Collaborative Research: NeTS: JUNO3: Towards an Internet of Federated Digital Twins (IoFDT) for Society 5.0: Fundamentals and Experimentation
合作研究:NetS:JUNO3:迈向社会 5.0 的联合数字孪生 (IoFDT) 互联网:基础知识和实验
- 批准号:
2210254 - 财政年份:2022
- 资助金额:
$ 110万 - 项目类别:
Standard Grant
NSF-AoF: Vision-Guided Wireless Communication Systems
NSF-AoF:视觉引导无线通信系统
- 批准号:
2225511 - 财政年份:2022
- 资助金额:
$ 110万 - 项目类别:
Standard Grant
Collaborative Research: CNS Core: Small: Hierarchical Federated Learning Over Wireless Edge Networks: Performance Analysis and Optimization
协作研究:CNS 核心:小型:无线边缘网络的分层联邦学习:性能分析和优化
- 批准号:
2114267 - 财政年份:2021
- 资助金额:
$ 110万 - 项目类别:
Standard Grant
SII Planning: ARIES: Center for Agile, RelIablE, Scalable Spectrum
SII 规划:ARIES:敏捷、可靠、可扩展频谱中心
- 批准号:
2037870 - 财政年份:2020
- 资助金额:
$ 110万 - 项目类别:
Standard Grant
EAGER: Collaborative Research: Modernizing Cities via Smart Garden Alleys with Application in Makassar City
EAGER:合作研究:通过智能花园巷实现城市现代化并在望加锡市应用
- 批准号:
2025377 - 财政年份:2020
- 资助金额:
$ 110万 - 项目类别:
Standard Grant
Collaborative Research: CNS Core: Small: Extended Reality over Wireless Cellular Networks: Quality-of-Experience Analysis and Optimization
合作研究:CNS 核心:小型:无线蜂窝网络上的扩展现实:体验质量分析和优化
- 批准号:
2007635 - 财政年份:2020
- 资助金额:
$ 110万 - 项目类别:
Standard Grant
CNS Core: Small: Collaborative: Towards Surge-Resilient Hybrid RF/VLC Networks
CNS 核心:小型:协作:迈向抗浪涌混合 RF/VLC 网络
- 批准号:
1909372 - 财政年份:2019
- 资助金额:
$ 110万 - 项目类别:
Standard Grant
ICE-T: RC: Towards Highly Reliable Low Latency Broadband (HRLLBB) Communications over Wireless Heterogeneous Networks
ICE-T:RC:通过无线异构网络实现高度可靠的低延迟宽带 (HRLLBB) 通信
- 批准号:
1836802 - 财政年份:2018
- 资助金额:
$ 110万 - 项目类别:
Standard Grant
CRISP Type 1/Collaborative Research: A Human-Centered Computational Framework for Urban and Community Design of Resilient Coastal Cities
CRISP 类型 1/协作研究:以人为本的弹性沿海城市城市和社区设计计算框架
- 批准号:
1638283 - 财政年份:2017
- 资助金额:
$ 110万 - 项目类别:
Standard Grant
BIGDATA: Collaborative Research: IA: Big Data Analytics for Optimized Planning of Smart, Sustainable, and Connected Communities
BIGDATA:协作研究:IA:用于智能、可持续和互联社区优化规划的大数据分析
- 批准号:
1633363 - 财政年份:2016
- 资助金额:
$ 110万 - 项目类别:
Standard Grant
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