CC*IIE Networking Infrastructure: Building a Science DMZ and Enhancing Science Data Movement to Support Data Intensive Computational Research at South Dakota State University
CC*IIE Networking Infrastructure: Building a Science DMZ and Enhancing Science Data Movement to Support Data Intensive Computational Research at South Dakota State University
批准号:
1440622
负责人:
Michael Adelaine
金额:
$49.45万
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:
2014-12-01 至 2016-11-30
中文摘要
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英文摘要
South Dakota State University's (SDSU) strategic plan, Impact 2018, challenges segments of the university to be high performing; research and innovation was singled out as one such area that would take up that challenge. In order to achieve this level of performance, the plan specifies that information technology be the foundation on which this success is built. With this in mind, the Division of Technology and Security has targeted the construction of a Science DMZ to enhance current end-to-end science data transfer scenarios and position university researchers to take advantage of the next generation in network connectivity for cross-institutional collaboration. The Science DMZ project is designed according to the architecture and practices established by the Energy Sciences Network (ESNET) to enable fast end-to-end transfers of scientific data and optimize network components for high-performance scientific applications. Specific elements of the Science DMZ include support for virtual circuits, software defined networking, network testing and enhancements in high-speed data transfer processing. The need for these cyberinfrastructure improvements are driven by increased levels of scientific activity across campus research areas, namely big data users found within the Geographic Information Science Center of Excellence (GSCE), the Image Processing Lab, and several groups within the Biology and Plant Science departments involved with state-of-the-art genomics processing and applications. This effort promises to transform SDSU's infrastructure, providing a coordinated resource to systematically process, transfer and analyze large science data sets, resulting in enhanced collaborative opportunities for the research community.
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