CC-NIE Networking Infrastructure: Data Driven Networking - Keeping SFA on the Map
CC-NIE Networking Infrastructure: Data Driven Networking - Keeping SFA on the Map
批准号:
1341010
负责人:
Michael Coffee
金额:
$49.73万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2013
资助国家:
美国
项目状态:
已结题
起止时间:
2013-09-01 至 2015-08-31
中文摘要
CC-NIE网络基础设施项目克服了Stephen F.奥斯汀州立大学(SFA),对网络基础设施、连接和科学DMZ进行了重大升级。这些升级支持扩展的研究和教学能力,并提高跨各种STEM学科的数据驱动研究的能力。正在建设的网络增强包括两个光纤安装版本,其中一个支持从SFA主校区到Internet 2和Lonestar教育和研究网络(LEARN)的受保护的10 Gb/s以太网连接,在休斯敦的存在和其他从SFA主校区到远程SFA天文台和沃尔特C。托德农业研究中心正在进行的升级将科学DMZ的容量从1 Gb/s提高到10 Gb/s,以便在大学的保护防火墙之外快速交换大型数据集。安装10 GB/s PerfSONAR节点后,SFA可以对相关站点的性能进行基准测试,并监控网络性能。应用包括物理学和天文学,农业,生物学,生物技术,化学,计算机科学,数学和统计学,林业和地理空间科学的研究工作,这些研究工作将直接受益于操纵,管理和传输较大数据集的能力。此外,增强的基础设施将提高校园、国家和全球合作研究的能力,并充分利用现有的网络,如LEARN、internet 2、REDDnet和AmericaView。网络的改进还将加强这些和其他STEM学科的研究生和本科生课程,并允许更多的学生参与数据密集型研究。
英文摘要
The CC-NIE Networking Infrastructure project overcomes geographical and technological barriers at Stephen F. Austin State University (SFA) with major upgrades to network infrastructure, connectivity, and the science DMZ. These upgrades support expanded research and teaching capabilities and improve capacity for data-driven research across a variety of STEM disciplines.Network enhancements under construction consist of two fiber optic installation builds, one enabling a protected 10 Gb/s Ethernet connection from the SFA main campus to the Internet2 and the Lonestar Education and Research Network (LEARN) point-of-presence in Houston and the other from the SFA main campus to the remote SFA Observatory and Walter C. Todd Agricultural Research complex. Upgrades in progress increase the capacity of the science DMZ from 1 Gb/s to 10 Gb/s to allow for the rapid exchange of large datasets outside of the university's protective firewall. Installation of a 10 GB/s PerfSONAR node allows SFA to benchmark performance to relevant sites and to monitor network performance. Applications include research endeavors in physics and astronomy, agriculture, biology, biotechnology, chemistry, computer science, mathematics and statistics, forestry, and geospatial sciences that will directly benefit from the ability to manipulate, manage, and transfer larger data sets. Additionally, the enhanced infrastructure will improve capacity for collaborative research on campus, nationally, and globally, and afford full use of existing networks, such as LEARN, internet2, REDDnet and AmericaView. The networking improvements will also enhance both graduate and undergraduate curricula in these and other STEM disciplines and allow for increased student participation in data-intensive research.
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