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

长期以来，通过在大学一级的研究基础设施上进行大量投资，可以实现从各个研究实验室到其他合作实验室和云资源的科学数据传输。然而，当一个研究实验室转移大型科学数据集时，研究和信息技术（IT）社区在为研究协作创建安全拓扑时仍然存在许多障碍。休斯顿大学的愿景是实现电路设置的抽象、流量控制和网络功能的利用，最终用户可以选择以定制的方式将他们的数据与研究人员实验室连接起来，并在拓扑上执行相关的数据共享策略。该项目：(1)在大学校园内具有研究实验室的战略建筑的主配线架（MDF）组件中部署网络功能实例化（NFI）；(2)为空气质量和医疗保健研究用例定制了一个跨学科数据共享隔离网络；(3)在Lonestar教育与研究网络（LEARN）上试点部署NFI功能，以支持未来的科学数据流。这项工作在许多方面都有广泛的影响：每个研究实验室的孤立网络为加速创新创造了一个环境，没有操作限制。提出的原型研究拓扑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。

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.