CC*IIE Networking Infrastructure: Enabling and Improving Data-Driven Research at Texas State University
CC*IIE Networking Infrastructure: Enabling and Improving Data-Driven Research at Texas State University
批准号:
1440637
负责人:
Xiao Chen
金额:
$49.99万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2014
资助国家:
美国
项目状态:
已结题
起止时间:
2014-10-01 至 2017-09-30
中文摘要
数据现在被编织到我们社会的每个部门和功能中。德克萨斯州的研究人员正在利用生物化学、生物学、地理学、计算机科学、财经、数学和信息系统等领域的大数据,率先解决一些最紧迫的挑战。尽管如此,目前德克萨斯州的网络基础设施和连接能力对涉及大数据的研究项目以及共享海量数据的多个机构之间的合作构成了障碍。该项目开发了一个高速园区网络基础设施,以支持和改进德克萨斯州的数据驱动研究。它支持即时的10 Gb能力和未来的100 Gb,并在园区网络上创建专门用于研究数据的科学DMZ,使研究人员能够以更快的速度通过网络与同行交换大型数据集。该基础设施增强并更好地促进了德克萨斯州多个学科的大数据研究,具有显著的社会效益,使德克萨斯州大学系统的所有其他成员机构能够建立类似的环境,以适应其研究和教育需求,推进研究和教育的整合,促进跨机构合作,并将显著增强德克萨斯州及其他地区目前的大数据研究和教学能力。
英文摘要
Data are now woven into every sector and function in our society. Texas State researchers are pioneering in solving some of the most pressing challenges using big data in the fields of Biochemistry, Biology, Geography, Computer Science, Finance and Economics, Mathematics, and Information Systems. Nonetheless, the current Texas State cyberinfrastructure and connectivity capacity present obstacles to the research projects involving big data and the collaborations among multiple institutions sharing massive amounts of data. This project develops a high-speed campus network infrastructure to enable and improve data-driven research at Texas State. It enables immediate 10Gb capability and 100Gb in the future, and creates a Science DMZ on the campus network dedicated to research data to allow researchers to exchange large datasets with their peers over the network at a much faster speed. The infrastructure enhances and better facilitates big data research across a wide range of disciplines at Texas State with notable societal benefits, enables all other Texas State University System member institutions to establish similar environments to accommodate their research and education needs, advances the integration of research and education, promotes cross-institutional collaborations, and will significantly enhance the current big data research and teaching capabilities at Texas State and beyond.
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