CC*DNI Networking Infrastructure: Custom Science DMZ Per Research Lab with a Secure Invitation to Opt-In

CC*DNI 网络基础设施：每个研究实验室的定制科学 DMZ，并提供安全选择加入邀请

• 批准号: 1541368
• 负责人: Deniz Gurkan
• 金额: $ 49.97万
• 依托单位: University of Houston
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1541368&HistoricalAwards=false
• 关键词: CC; DNI; Networking; Infrastructure; Custom

Science data transfers originating from various research labs to other collaborating labs and cloud resources have long been enabled by significant investments in research infrastructure at the university level. However, when a research lab transfers large scientific data sets, many hurdles still exist for research and Information Technology (IT) communities to work together in creating secure topologies for research collaboration. The University of Houston's vision is to enable the abstraction of circuit setup, traffic steering, and leveraging of network functionality for end-users to opt-in to connect their data with researcher labs in a customized fashion with relevant data sharing policies enforced on the topology. This project: (1) deploys network function instantiation (NFI) within main distribution frame (MDF) components at strategic buildings with research labs on university campuses; (2) implements an interdisciplinary data sharing isolated network customized for an air quality and healthcare research use case; and (3) deploys the NFI capability as a pilot on LEARN (Lonestar Education and Research Network) for future support of science data flows.This work has a broad impact across many dimensions: isolated networks per research lab creates an environment for accelerated innovation, free of operational constraints. The proposed prototype research topology supports researchers in eliminating the data sharing problems, with concepts that extend to all research collaborations.

科学数据从各个研究实验室传输到其他合作实验室和云资源，长期以来一直是通过对大学研究基础设施的大量投资来实现的。然而，当研究实验室传输大型科学数据集时，研究和信息技术（IT）社区在为研究协作创建安全拓扑方面仍然存在许多障碍。 休斯顿大学的愿景是实现电路设置、流量引导和网络功能的抽象化，以便最终用户选择以定制的方式将其数据与研究实验室连接，并在拓扑上实施相关的数据共享策略。本项目：（1）在大学校园内具有研究实验室的战略建筑物处的主配线架（Main Distribution Frame，简称DAF）组件内部署网络功能实例化（Network Function Instantiation，简称NFI）;（2）实现针对空气质量和医疗保健研究用例定制的跨学科数据共享隔离网络;以及（3）部署NFI能力作为LEARN上的试点（Lonestar教育和研究网络），以支持未来的科学数据流。这项工作在许多方面产生了广泛的影响：每个研究实验室的独立网络为加速创新创造了一个无运营限制的环境。所提出的原型研究拓扑结构支持研究人员消除数据共享问题，其概念扩展到所有研究合作。