CC* Integration-Small: Science Traffic as a Service (STAAS)

CC* 集成 - 小：科学流量即服务 (STAAS)

基本信息

批准号：
2018308
负责人：
John Brassil
金额：
$ 51.42万
依托单位：
Princeton University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2020
资助国家：
美国
起止时间：
2020-10-01 至 2024-09-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2018308&HistoricalAwards=false
关键词：
CC Integration Small Science Traffic

项目摘要

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 the 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, this project 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. The proposed work 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. 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. All documents, software, presentations, and other artifacts created under this project will be made publicly available at http://www.cs.princeton.edu/~jbrassil/public/projects/staas/The key project insight is that many science flows are already in transit at any moment on or between 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.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.

科学研究的未来进步将需要对海量数据集和高带宽流科学仪器数据进行计算。需要新的实验研究基础设施来促进对能够支持这些日益要求的科学数据流的网络的理解。使用实际的高速科学数据流量测试网络技术和协议的进步对于网络实验人员、科学仪器用户和数据科学家至关重要。为了满足这一需求，该项目将开发一个去中心化计算和网络系统的原型，以创建、收集并向实验研究基础设施用户社区分发各种真实和合成科学流量。拟议的工作将首先在连接两所美国大学的网络编程倡议测试平台上开发和部署科学流量即服务 (STAAS) 原型，然后为 STAAS 做好准备，以便在目前正在开发的 FABRIC 中型网络研究基础设施上进行全国部署。参与具有严格科学流量工作量的网络测试台研究的学生将学习技能，以帮助加强劳动力队伍，以推进全球规模的计算云应用服务平台，这些平台对美国经济越来越重要。该项目下创建的所有文档、软件、演示文稿和其他工件都将在 http://www.cs.princeton.edu/~jbrassil/public/projects/staas/ 上公开提供。该项目的关键见解是许多科学流程随时已经在校园内或校园之间运输。使用新的园区网络基础设施，包括无源光学测试接入点、网络数据包代理和数据平面可编程以太网交换机，STAAS 将安全地将这些流的副本转发到实验测试台上，同时保留流和数据的时序完整性他们的有效负载的隐私。大规模、高带宽实验将通过多个园区的许多或全部 STAAS 边缘节点的参与来实现。通过引入基于服务的模型，STAAS 可以帮助推进网络研究界新兴科学数据的传输，并帮助科学仪器的运营商提高其仪器收集的数据的数量和质量。该奖项反映了 NSF 的法定使命，并已通过使用基金会的智力优点和更广泛的影响审查标准进行评估，认为值得支持。