CC* Integration-Large: An 'On-the-fly' Deeply Programmable End-to-end Network-Centric Platform for Edge-to-Core Workflows

无人机(也被称为无人机)正在天空中变得越来越流行。它们的应用范围从用于休闲活动的业余爱好无人机，到用于器官运输的至关重要的生命无人机，再到商业应用，如空中出租车。这类无人机的安全、高效和经济运行带来了科学界必须应对的各种挑战。例如，无人机需要非常详细、贴近地面的天气信息才能安全运行，无人机的数据处理和能耗需要智能化处理。该项目将提供工具，允许研究人员和无人机应用程序开发人员通过使用先进的计算机和网络技术来应对无人机操作挑战。该项目将提供一个架构和工具，使科学家能够将边缘计算设备纳入他们的计算工作流程。此功能对于无人机视频分析和无人机路线规划等低延迟和超低延迟应用至关重要。拟开展的工作包括四项主要工作。首先，尖端的网络和计算基础设施将集成到整体架构中，使其成为科学工作流程的一部分。第二，将通过新的编程抽象实现网络边缘和核心的网络内处理。第三，将提供增强的端到端监控能力。最后，该架构将利用Pegasus工作流管理系统集成网络内和边缘处理能力。从长远来看，提供最佳实践和工具，使先进的网络基础设施能够用于科学工作流，将对社会产生广泛影响。该项目将支持的科学驱动因素有可能提高无人机应用的安全性和效率，这一领域在可预见的未来将变得越来越重要。项目小组将使来自不同机构(历史上的黑人学院和大学、社区学院、女子学院)的研究人员和教育工作者能够获得丰富的资源，以进一步实现研究的民主化。此外，与NSFREU(本科生研究体验)网站在消费者网络方面的合作将促进未得到充分服务/代表不足的学生参与项目活动。有关该项目的信息将在http://www.flynet-ci.org上提供，以提供有关整个项目活动、外联活动、出版物、工具和软件以及该项目团队成员的信息。项目网站将在项目结束后保留至少三年。这一奖项反映了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。

Unmanned Aerial Vehicles (also known as drones) are becoming popular in the sky. Their application reaches from hobby drones for leisurely activities to life-critical drones for organ transport to commercial applications such as air taxis. The safe, efficient, and economic operation of such drones poses a variety of challenges that have to be addressed by the science community. For example, drones need very detailed, close to the ground weather information for safe operations, and data processing and energy consumption of drones need to be intelligently handled. This project will provide tools that will allow researchers and drone application developers to address operational drone challenges by using advanced computer and network technologies.This project will provide an architecture and tools that will enable scientists to include edge computing devices in their computational workflows. This capability is critical for low latency and ultra-low latency applications like drone video analytics and route planning for drones. The proposed work will include four major tasks. First, cutting edge network and compute infrastructure will be integrated into the overall architecture to make them available as part of scientific workflows. Second, in-network processing at the network edge and core will be made available through new programming abstractions. Third, enhanced end-to-end monitoring capabilities will be offered. Finally, the architecture will leverage the Pegasus Workflow Management System to integrate in-network and edge processing capabilities.Providing best practices and tools that enable the use of advanced cyberinfrastructure for scientific workflows will have a broad impact on society in the long term. The science drivers that will be supported by this project have the potential to increase the safety and efficiency of drone applications, an area that will grow in significance in the foreseeable future. The project team will enable access to a rich set of resources for researchers and educators from a diverse set of institutions (historically black colleges and universities (HBCU), community colleges, women’s colleges) to further democratize research. In addition, collaboration with the NSF REU (Research Experience for Undergraduates) Site in Consumer Networking will promote participation of under-served/under-represented students in project activities.Information about the project will be available at http://www.flynet-ci.org to provide information on overall project activities, outreach activities, publications, tools and software, and the project’s team members. The project website will be preserved for at least three years after the project ends.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.