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

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.