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

CC* 集成 - 小：科学流量即服务 (STAAS)

• 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

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.

未来科学研究的进步将需要对海量数据集和高带宽流式科学仪器数据进行计算。将需要新的实验研究基础设施来促进对能够支持这些日益苛刻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。为了满足这一需要，该项目将开发一个分散计算和联网系统的原型，以创建、收集和向实验研究基础设施用户社区分发各种真实和合成的科学流量。拟议的工作将首先在连接两所美国大学的网络编程倡议试验台上开发和部署科学流量即服务(STaaS)原型，然后准备STaaS，以便稍后在目前正在开发的Fabric中型网络研究基础设施上进行全国部署。接触到具有苛刻科学流量工作负荷的网络试验台研究的学生将学习技能，以帮助加强准备推进全球规模的计算云应用服务平台的劳动力，这些平台对美国经济日益重要。在该项目下创建的所有文档、软件、演示文稿和其他人工制品将在http://www.cs.princeton.edu/~jbrassil/public/projects/staas/The上公开可用。使用新的园区网络基础设施，包括无源光测试接入点、网络数据包代理和数据平面可编程以太网交换机，STaaS将安全地分流并将这些流的副本转发到实验试验台，同时保护流的时序完整性及其有效负载的数据隐私。通过招募多个校区中的多个或所有STaaS边缘节点参与，将实现大规模、高带宽的实验。通过引入基于服务的模式，STaaS可以帮助推进网络研究社区传输新兴科学数据，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。

项目成果

Experience-driven research on programmable networks

• DOI: 10.1145/3457175.3457178
• 发表时间: 2021-01
• 期刊: ACM SIGCOMM Computer Communication Review
• 影响因子: 2.8
• 作者: Hyojoon Kim;Xiaoqi Chen;J. Brassil;J. Rexford