CC*IIE Region: Transforming a Regional Network and the Regional Community to Serve Diverse and Emerging Research Needs
CC*IIE Region: Transforming a Regional Network and the Regional Community to Serve Diverse and Emerging Research Needs
批准号:
1440450
负责人:
Paul Schopis
金额:
$15.0万
依托单位:
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 2017-08-31
中文摘要
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英文摘要
With the ever-increasing cyberinfrastructure needs of science in an era of "Big Data", many campuses and regional networks are ill prepared to deal with the requirements researchers need to carry out their work. Some solid progress has been made in areas of campus infrastructure, but all too often these efforts fall short. In general, backbone networks at both the regional and national levels are competently run. However, frequently it is the case that many hours of troubleshooting across the campus, regional and national networks are required to get good performance and often require many hours of work by multiple staffs at multiple organizations.There are two issues at the regional network level being addressed. The first issue is knowledge exchange and best practice. Having staff at each layer of the campus, regional and national layer equipped with correct skill sets and resources to call upon for resolution is paramount. In the latter case, the resources include the "human network", specifically,a network of individuals at the campus and regional level to function collaboratively. Secondly, having a widely deployed and easily accessible monitoring and measurement infrastructure is required for success.OARnet is convening a forum for regional stakeholders to articulate needs, solutions and best practices via a workshop series. Secondly, OARnet is providing technical engagement and knowledge exchange directly with stakeholders and is developing the "human network" of support amongst the stakeholders. Thirdly OARnet is deploying perfSonar widely throughout the Ohio Academic Resources Network (OARnet) infrastructure, for highly granular data collection.
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