CCRI: Planning-C: Federated Cloud Platform for Networked Cyber Physical Systems Research

网络化网络物理系统(NCP)通过有效地控制和管理关键服务，在现代社会中发挥着至关重要的作用。与传统的网络物理系统(CP)相比，这种N-CP具有明显的优势，包括易于使用和控制、更好的服务和系统管理、更好的资源利用率、使用商用现成(COTS)组件的能力，以及以增加复杂性为代价提高可靠性和容错服务。采用N-CPS增加了网络安全、系统开发、系统管理和培训方面的挑战，需要一个联合云平台来支持协作N-CPS研究。这一网络网络物理系统联合云平台(FCP-NCPS)将使研究人员能够解决N-CPS的安全、互操作性、管理和培训挑战，同时为数据分析和网络安全研究创建现实的数据集。这项规划拨款将使：1)在图森地区、巴尔的摩地区和底特律地区组织研究社区和行业研讨会，讨论需求并交流可通过FCP-NCPS解决的研究想法；2)与图森、巴尔的摩和底特律地区的教学和K-12学校组织研讨会，讨论和了解他们向学生传授CPS培训的需求。这些活动将允许：1)创建一个社区云平台，用于无缝集成句法、语义和地理上分离的各种CPS试验台，以进行现实的实验，以应对N-CPS的安全、互操作性、管理和培训挑战；2)开发一个整合到联邦系统中的数据集收集框架，以解决网络安全和数据分析领域中现实数据集的稀缺问题；3)提供社区基础设施，为学生提供现实的、实用的(动手)培训，以满足国家N-CPS劳动力的需求。FCP-NCPS作为一个可扩展的社区研究平台，还将在不同领域找到应用，包括扩展人工智能(AI)的可解释性和可信度，医疗器械和医疗培训实践的实验，以及自主系统的实验和发展，等等。此外，拟议的联合云平台将帮助全球研究社区(特别是发展中国家)进行现实的实验，并评估他们的研究想法，以推动科学的前沿。有关联邦云平台的信息，请访问https://fcpncps.arizona.edu.该网站将托管FCP-NCPS的所有内容，包括项目信息、API、文档和数据集，在项目持续时间和终止后三年内。该项目是亚利桑那大学、底特律大学、约翰霍普金斯大学和河滨研究学院的合作项目。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。

Networked Cyber-Physical Systems (NCPS) play an essential role in modern society by efficiently controlling and managing critical services. Such N-CPS' have noticeable advantages over traditional Cyber-Physical Systems (CPS), including ease of use and control, better services and system management, better resource utilization, ability to use Commercial Off The Shelf (COTS) components, and improved reliability and fault-tolerant services at the cost of increased complexity. Adopting N-CPS adds challenges in cybersecurity, system development, systems management, and training, necessitating a federated cloud platform to support collaborative N-CPS research. This Federated Cloud Platform for Networked Cyber-Physical Systems (FCP-NCPS) will enable researchers to address N-CPS security, interoperability, management, and training challenges while enabling the creation of realistic datasets for research in data analytics and cybersecurity.This planning grant will enable: 1) to organize research community and industry workshops in the Tucson Area, Baltimore Area, and Detroit Area to discuss the needs and exchange research ideas addressable through the FCP-NCPS; 2) Organizing workshops with teaching and K-12 schools in Tucson, Baltimore, and Detroit areas to discuss and understand their needs to impart training in CPS to their students. These activities will allow: 1) Creation of a community cloud platform for seamless integration of diverse CPS testbeds that are syntactically, semantically, and geographically separated for realistic experimentation to address N-CPS security, interoperability, management, and training challenges; 2) to develop a dataset collection framework integrated into the federated system to address the scarcity of realistic datasets in the fields of cybersecurity, and data analytics; 3) to provide a community infrastructure for imparting realistic, practical (hands-on) training to students to address the nation's N-CPS workforce requirements.The FCP-NCPS being a scalable community research platform, will also find applications in different fields, including expanding interpretability and the trustworthiness of Artificial Intelligence (AI), experimentation of medical devices and medical training practices, and experimentation and evolution of autonomous systems, to name a few. Moreover, the proposed Federated Cloud Platform will aid the global research community (especially in the developing world) in performing realistic experimentation and evaluating their research ideas to advance the frontiers of science.Information on FCP-NCPS is available at https://fcpncps.arizona.edu. This site will host all the content for the FCP-NCPS, including the project information, APIs, documentation, and datasets, for the duration of the project and three years after its termination. This project is a collaboration between the University of Arizona, University of Detroit-Mercy, Johns Hopkins University, and Riverside Research.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.