CNS Core: Small: Collaborative: Coalescent Computing - New Theory, Mechanism and Platform for Adaptive Edge Computing

通过将计算转移到互联网的边缘，新兴的边缘计算模型有望减少应用程序响应时间，改善用户体验，节省带宽成本，并增强数据隐私。本项目将建立一种新的边缘计算理论，称为合并计算，每个应用程序运行在一个集成的虚拟计算系统上，该系统由边缘设备和云资源组成，根据运行时条件共同支持应用程序的执行。本研究将建立边缘云资源共享的新框架，探索各种实现机制，部署硬件平台进行实验研究，开发软件工具将现有应用程序转换为其合并计算版本，并进行两个案例研究。其目标是使用户应用程序能够无缝地克服边缘设备的资源限制，同时保持边缘计算承诺的低响应时间、减少通信和数据隐私的好处。这项工作解决了对自适应边缘计算通用理论的迫切需求，并提供了具体的实现机制，允许现有应用程序利用边缘计算而无需完全重新设计。所提出的合并计算框架及其软件工具提供了一种将现有应用程序代码转换为分布式软件的方便方法，具有增强的性能、响应时间、鲁棒性和可扩展性，这些都有助于更好的用户体验。理论与实验相结合的研究将促进我们对现代边缘计算系统的理解。该项目开发的所有软件工具都将开放源代码，以帮助促进其他相关研究。该项目还包括一项教育计划，将边缘计算引入本科/研究生课程，从代表性不足的学生群体中招募学生，并帮助当地高中的俱乐部活动。该奖项反映了美国国家科学基金会的法定使命，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。

By moving computation to the edge of the Internet, the emerging edge computing model promises to reduce application response time, improve user experience, save bandwidth cost, and enhance data privacy. This project will establish a new edge-computing theory called coalescent computing, where each application program runs on an integrated virtual computing system, consisting of resources from both edge devices and the cloud, which jointly support application execution according to run-time conditions. The proposed research will establish a novel framework of edge-cloud resource sharing, explore various implementation mechanisms, deploy a hardware platform for experimental studies, develop software tools to transform existing applications to their coalescent-computing versions, and carry out two case studies. Its objective is to enable user applications to seamlessly overcome the resource limitation of edge devices, while keeping the benefits of low response time, communication reduction, and data privacy that edge computing promises.This work addresses the pressing need for a generic theory of adaptive edge computing, with concrete implementation mechanisms that allow existing applications to take advantage of edge computing without complete re-design. The proposed coalescent-computing framework and its software tools offer a convenient way of transforming existing application code into distributed software with enhanced performance, response time, robustness and scalability, which all contribute to better user experience. The integrated theoretical and experimental research will advance our understanding of modern edge-computing systems. All software tools developed from this project will be made open-source to help stimulate other related research. The project also includes an education plan that introduces edge computing into undergraduate/graduate courses, recruits from under-represented student groups, and helps in club activities at the local high school.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.