EAGER: Distributed Models and Algorithms for Pervasive Systems

EAGER：普适系统的分布式模型和算法

• 批准号: 2336665
• 负责人: Gurdip Singh
• 金额: $ 25.85万
• 依托单位: George Mason University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-12-01 至 2025-11-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2336665&HistoricalAwards=false
• 关键词: EAGER; Distributed; Models; Algorithms; Pervasive

Development of pervasive computing infrastructure is crucial for enabling the next generation of applications wherein physical- and cyber-subsystems collaborate to achieve a common goal. In a pervasive distributed system (PDS), the cyber-infrastructure algorithms must contend with cyber and physical entities interacting directly with each other in multiple ways. Such interactions pose several new challenges in designing the underlying infrastructure algorithms. A number of assumptions related to when, where and how entities interact which typically hold in traditional systems may not apply in a PDS. The goal of this project is to develop new models and techniques to design distributed algorithms and middleware that can accommodate both cyber and physical entities in a PDS application.To develop models and distributed algorithms for pervasive systems this project will extend the traditional graph-based distributed computing models to create a unified model to capture interactions between the physical and cyber entities and the physical phenomena, develop algorithms for coordination and cooperation in PDS applications, and techniques to ensure that algorithms can perform reliably in environments where physical entities may behave unpredictably. This project will integrate the proposed model into existing simulation tools to enable evaluation of scenarios involving different types of physical entities and physical phenomena.Leveraging the capabilities of pervasive systems will be critical in supporting the needs of businesses and organizations. This research will lead to better understanding of distributed algorithms, and increase the confidence of businesses and organizations in using capabilities of next generation systems. This project will include integration of research and education, and outreach activities such as engagement with high school students for summer internships.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.

普适计算基础设施的发展是至关重要的，使下一代的应用程序，其中物理和网络子系统合作，以实现一个共同的目标。在普适分布式系统（PDS）中，网络基础设施算法必须与以多种方式相互直接交互的网络和物理实体竞争。这种交互在设计底层基础设施算法时提出了几个新的挑战。在传统系统中通常存在的与实体何时、何地和如何交互有关的许多假设可能不适用于PDS。该项目的目标是开发新的模型和技术，以设计分布式算法和中间件，可以容纳在PDS应用程序中的网络和物理实体。为了开发普适系统的模型和分布式算法，该项目将扩展传统的基于图的分布式计算模型，以创建一个统一的模型来捕获物理和网络实体以及物理现象之间的交互，开发PDS应用程序中的协调和合作算法，以及确保算法在物理实体可能无法预测的环境中可靠执行的技术。本项目将把建议的模型整合到现有的模拟工具中，以便对涉及不同类型物理实体和物理现象的情景进行评估。利用普及系统的功能对支持企业和组织的需求至关重要。这项研究将有助于更好地理解分布式算法，并增加企业和组织使用下一代系统功能的信心。该项目将包括研究和教育的整合，以及与高中生进行暑期实习等外联活动。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。