CC* Networking Infrastructure: Improving Network Infrastructure to Enable Large Scale Scientific Data Flows and Collaboration

校园网络需要保护信息和检查数据流，以保障安全和隐私。然而，研究人员需要开放和不受限制地访问地球仪的大型数据流和仪器，以缩短发现时间。 莱斯大学网络是一个共享资源，不仅需要支持行政和教学功能，而且还使科学家能够以新的创新方式使用该网络进行研究。 五个关键的数据密集型应用程序小组充当网络功能新扩展的驱动程序，并向技术设计人员提供反馈。 这些应用领域包括地球和大气科学;城市数据科学;计算生物科学和神经工程;粒子物理学和分布式集群计算。 这些应用建立在长期科学投资的基础上，旨在了解地震事件，海湾地区及其他地区的天气模式，以及德克萨斯州休斯顿等大型多元化城市的城市趋势。该项目采用的基本模式是“科学DMZ”。“科学DMZ”是网络的一部分，建立在校园本地网络周边或附近，旨在为高性能科学应用程序而不是通用业务系统优化设备、配置和安全策略。“这种方法使赖斯能够积极升级其网络能力，大大提高科学数据的访问。该项目支持我们的校外数据中心的数据传输设施与国家和国际R E数据存储库之间的100 GB/s流量，并利用SDN（Openflow）机制。

Campus networks are required to protect information and inspect data flows to safeguard security and privacy. However, researchers need open and unfettered access to large data flows and instruments across the globe to reduce time to discovery. The Rice University network is a shared resource that not only needs to support the administrative and teaching functions but also enable scientists to use that network in new and innovative ways for research. Five key data-intensive application teams act as drivers of the new extension of network functionality and are providing feedback to the technical design staff. These application areas include earth and atmospheric sciences; urban data science; computational biosciences and neuroengineering; particle physics and distributed cluster computing. These applications build on long-term science investments aimed, amongst others, at understanding seismic events, the weather patterns in the Gulf regions and beyond, as well as urban trends in large, diverse cities such as Houston, TX. The basic model adopted by the project is "the science DMZ." A Science DMZ is "a portion of the network, built at or near the campus local network perimeter designed so that equipment, configuration, and security policies are optimized for high-performance scientific applications rather than for general-purpose business systems." This approach allows Rice to aggressively upgrade its network capacity for greatly enhanced science data access. This project supports 100 GB/s flows between the data transfer facilities at our off-campus data center and national and international R&E data repositories and takes advantage of SDN (Openflow) mechanisms.