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Data-Driven Networking Infrastructure: The Development of Cyberinfrastructure to Support Scientific and Engineering Research at West Virginia University

Data-Driven Networking Infrastructure: The Development of Cyberinfrastructure to Support Scientific and Engineering Research at West Virginia University
数据驱动的网络基础设施:西弗吉尼亚大学支持科学和工程研究的网络基础设施的开发
批准号:
1440655
负责人:
EARL SCIME
金额:
$48.69万
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:
2014-09-01 至 2015-08-31

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中文摘要
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英文摘要
West Virginia University (WVU) is, with the support of the National Science Foundation's Campus Cyberinfrastructure - Infrastructure, Innovation and Engineering program, deploying a new campus cyberinfrastructure architecture. This new architecture is specifically designed to support, foster and advance scientific and engineering research and discovery through the implementation of a high performance research data networking infrastructure. This project capitalizes on previous investments in a high performance campus network backbone and creates high performance end-to-end connectivity between the campus core and critical scientific and engineering research and education assets. More specifically, the WVU project team is 1) creating high speed connectivity between the campus network core and its Genomics Core research facility, the astrophysics analysis center, its neuroscience research program, and the Science, Technology, Engineering and Math (STEM) Education Lab; 2) implementing a science DMZ (a science "express lane") within the campus network for high performance science application data transfers; and 3) establishing a data transfer node to serve as a high performance end-point for large scale transfers of scientific data.This effort will result in high performance end-to-end bandwidth connecting these research assets to the campus network backbone, and in turn, connecting them to the research community and other resources across campus and to the international research and education network infrastructure. This will enable new levels of data-driven science that have been difficult if not infeasible to carry out at WVU.
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