EAGER: Duke ON-RAMPS: OpenFlow-Enabled Network Resource Access that is Manageable, Programmatic, and Safe

该项目将部署一个试点软件定义科学网络（SDSN），以互连杜克校园的研究计算资源，并将其链接到国家广域网电路结构。 这一试点部署将支持计算机科学应用程序（如GENI）和领域科学（如杜克的基因组科学与政策研究所（IGSP）和杜克的高能物理组（HEP））。 此外，SDSN将连接到杜克共享集群资源（DSCR），这是一个由杜克校园内的领域科学家使用的4300核共享批处理作业服务。 其主要目标是使领域科学家能够请求虚拟网络，这些虚拟网络是科学网络的"简单且可扩展的飞地"，并且将校园内的选定资源与校园外的选定资源链接起来，同时排除不相关的流量。该项目将在SDSN的隔离流空间切片内试用OpenFlow控制器，包括启用OpenFlow的流量工程策略，将科学流量卸载到SDSN上。 该项目计划是，最初的试验演示将行使cloudbursting能力，将计算服务扩展到云站点，并（可能）支持虚拟机迁移之间的OpenStack云测试床在校园。主要研究员将在技术文件中报告其经验。 差旅预算包括向其他大学CIO/CTO介绍学习情况。 尽管软件定义网络（SDN）技术目前正在被广泛讨论，并且是GENI架构中的关键元素，但使用它们的操作或校园级架构经验很少。 该项目将推进SDN技术与校园网络的集成，并在校园内和跨校园实现科学资源和GENI资源的安全，可控互连。该项目旨在设计和实施实用的解决方案，这些解决方案在初始原型之外易于复制，可扩展到更广泛的用途，并以（或很快将成为）坚实，可管理和商业化的技术为基础，可用于整个生产园区网络的部署。该项目的成果包括向其他校园网络运营商、SDN研究人员和业界报告结果和经验教训。更广泛的影响：该试点将提供一个机会，让人们在校园环境中获得OpenFlow的架构、部署、管理和运营问题方面的经验，以满足计算机科学领域以外的研究和教育需求。 杜克校园OpenFlow模型（GENI衍生技术）为领域科学提供了对超高速网络的按需访问，而没有性能限制防火墙。 因此，它将为领域科学提供直接利益。 PI将报告与部署相关的问题和操作经验。 这些报告和PI愿意与其他大学分享他们的经验，将减少校园使用GENI的障碍，建立GENI技术和OpenFlow作为科学网络的构建模块，加强对杜克校园计算科学的支持，并促进科学研究人员及其合作者之间的资源和数据共享。

This project will deploy a pilot Software-Defined Science Network (SDSN) to interconnect research computing resources on the Duke campus and link them to national WAN circuit fabrics. This pilot deployment will support both Computer Science applications such as GENI and domain sciences such as Duke's Institute for Genome Sciences and Policy (IGSP) and Duke's high-energy physics group (HEP). Additionally, the SDSN will connect to the Duke Shared Cluster Resource (DSCR), a 4300-core shared batch job service used by domain scientists all over the Duke campus. The key goal is to enable domain scientists to request virtual networks that are 'simple and scalable enclaves' for science networking, and that link selected resources on campus with selected resources outside, while excluding unrelated traffic.The project will experiment with OpenFlow controllers on a trial basis within isolated flowspace slices of the SDSN, including OpenFlow-enabled traffic engineering policies that offload science traffic onto the SDSN. The project plan is that initial trial demos will exercise cloudbursting capability to expand computing service into a cloud site, and (potentially) to support virtual machine migration among the OpenStack cloud testbeds on campus. The PIs will report on their experience in technical papers. Travel budget is included for presentation of learnings to other university CIO/CTOs. Although software-defined networking (SDN) technologies are currently being widely discussed and are key elements in the GENI architecture, there is little operational or campus-level architectural experience with using them. The project will advance the state of the art in integrating SDN technologies into campus networks, and in enabling safe, controlled interconnection of science resources and GENI resources within and across campuses. The project seeks to devise and implement practical solutions that are easily reproducible beyond the initial prototype, scalable to wider use, and grounded in technologies that are (or soon will be) solid, manageable, and commercially available for deployment throughout production campus networks. The project outcomes include reporting of results and lessons to other campus network operators and to SDN researchers and industryBroader Impact:The pilot will provide an opportunity to gain experience with architectural, deployment, administrative and operational issues of OpenFlow in campus settings to serve research and education needs beyond the Computer Science domain. The Duke campus OpenFlow model (GENI-derived technology) offers domain sciences on-demand access to ultra-high-speed networks without performance limiting firewalls. As such it will provide direct benefit to the domain sciences. The PIs will report on issues and operational experience associated with the deployment. These reports and the PI's willingness to share their experience with other universities will reduce barriers to use of GENI from campuses, establish GENI technologies and OpenFlow as building blocks for science networking, enhance support for computational science on the Duke campus, and facilitate sharing of resources and data among science researchers and their collaborators on and off campus.