Science Traffic as a Service

Jack Brassil, Jennifer Rexford, Joon Kim

Summary

Future advances in scientific research will require computing on massive datasets and high bandwidth streaming scientific instrument data. New experimental research infrastructures will be required to advance our understanding of the networks capable of supporting these increasingly demanding science data flows. Testing advances in networking technologies and protocols with actual high-speed science data traffic is vital to networking experimenters, scientific instrument users, and data scientists.

To address this need we will develop a prototype of a decentralized computing and networking system to create, collect and distribute a diverse collection of real and synthetic science traffic flows to the experimental research infrastructure user community. We will first develop and deploy the Science Traffic as a Service (STAAS) prototype on the Network Programming Initiative testbed connecting two US universities, and then prepare STAAS for later nationwide deployment on the FABRIC midscale networking research infrastructure now under development.

Our key project insight is that many science flows are already in transit at any moment on or betweeen campuses. Using new campus cyberinfrstucture including passive optical Test Access Points, Network Packet Brokers, and data-plane programmable ethernet switches, STAAS will safely tap and forward copies of these flows onto the experimental testbed, while preserving both the timing integrity of the flows and the data privacy of their payloads. Large scale, high bandwidth experiments will be achieved by enlisting participation of many or all STAAS edge nodes on multiple campuses. By introducing a service-based model STAAS can help advance the networking research community's transport of emerging science data, and help the operators of scientific instruments increase the amount and quality of data collected by their instruments.

The students exposed to research on networking testbeds with demanding science traffic workloads will learn skills to help strengthen a workforce prepared to advance the global-scale computing cloud application service platforms that are increasingly central to the US economy.

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This project is supported in part by the National Science Foundation under grant OAC-2018308