CC* Networking Infrastructure: FAN4Science: Flow-Aware Networking for Data-Intensive Science

CC* 网络基础设施：FAN4Science：数据密集型科学的流感知网络

• 批准号: 2346681
• 负责人: Shafaq Chaudhry
• 金额: $ 65万
• 依托单位: The University of Central Florida Board of Trustees
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-04-01 至 2026-03-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2346681&HistoricalAwards=false
• 关键词: CC; Networking; Infrastructure; FAN4Science; Flow

Democratizing access to local, regional, and national supercomputing facilities is essential for researchers to meet their increasingly data-intensive science objectives. Furthermore, research is exceedingly collaborative with national or global research teams studying phenomena like global pandemic, climate change, smart cities, and exploring the universe's secrets. These objectives can be achieved through high-speed connectivity to powerful computing platforms through the interconnected web of research and education networks. The FAN4Science project brings together experts in network engineering, campus IT, and regional network providers to address research and development challenges of enabling a high-throughput and flexible network for University of Central Florida (UCF)'s researchers. The scientific merit of this project is to explore the use of flow-aware networking methods to increase effective capacity of a campus network for researchers while also enabling innovative research in computer networking. The project (a) builds a 100Gbps research network to enable targeted research labs to get high-speed access to UCF's advanced computing facility; (b) installs performance monitoring and data transfer nodes at key locations to monitor research data movement; (c) augments the campus network with a Software-Defined Networking (SDN) setup for UCF research and teaching activities; and (d) enables experimental SDN research, utilizing real traffic, that explores speculative flow installations to reduce end-to-end latency. The project offers research opportunities to UCF graduate students and hands-on learning experience with installing real networking and performance monitoring equipment. Lessons learned have the potential to evolve into an SDN-controlled campus network design that can handle regular campus traffic and research traffic.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.

民主化地使用地方、区域和国家超级计算设施对于研究人员实现其日益数据密集的科学目标至关重要。此外，研究与国家或全球研究团队密切合作，研究全球大流行、气候变化、智能城市和探索宇宙的秘密等现象。这些目标可以通过互联的研究和教育网络高速连接到强大的计算平台来实现。FAN 4Science项目汇集了网络工程、校园IT和区域网络提供商方面的专家，旨在解决为中佛罗里达大学（UCF）的研究人员实现高吞吐量和灵活网络的研发挑战。这个项目的科学价值是探索使用流量感知网络方法来增加研究人员的校园网络的有效容量，同时也使计算机网络的创新研究成为可能。该项目（a）建立一个100 Gbps的研究网络，使目标研究实验室能够高速访问UCF的先进计算设施;（B）在关键位置安装性能监测和数据传输节点，以监测研究数据的移动;（c）为UCF的研究和教学活动设置软件定义网络，以增强校园网络;以及（d）利用真实的业务，实现实验性SDN研究，其探索推测性流安装以减少端到端延迟。该项目为UCF研究生提供研究机会，并通过安装真实的网络和性能监控设备获得实践学习经验。所吸取的经验教训有可能演变成SDN控制的校园网络设计，可以处理常规的校园流量和研究流量。该奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。