Cloud computing in e-Science: research challenges and opportunities

被引:0
|
作者
Xiaoyu Yang
David Wallom
Simon Waddington
Jianwu Wang
Arif Shaon
Brian Matthews
Michael Wilson
Yike Guo
Li Guo
Jon D. Blower
Athanasios V. Vasilakos
Kecheng Liu
Philip Kershaw
机构
[1] University of Reading,Reading e
[2] Computer Network Information Centre,Science Centre
[3] Chinese Academy of Sciences,Oxford e
[4] University of Oxford,Research Centre
[5] Centre for e-Research,Scientific Computing Department
[6] King’s College London,Department of Computing
[7] San Diego Supercomputer Center,Department of Computer and Telecommunications Engineering
[8] University of California,Informatics Research Centre
[9] Rutherford Appleton Laboratory,undefined
[10] STFC,undefined
[11] Imperial College London,undefined
[12] University of Western Macedonia,undefined
[13] University of Reading,undefined
[14] NCEO/Centre for Environmental Data Archival,undefined
[15] Rutherford Appleton Laboratory,undefined
[16] STFC,undefined
来源
关键词
e-Science; e-Research; Informatics; Cloud computing; Semantic web; Grid computing; Workflow; Digital research; Big data;
D O I
暂无
中图分类号
学科分类号
摘要
Service-oriented architecture (SOA), workflow, the Semantic Web, and Grid computing are key enabling information technologies in the development of increasingly sophisticated e-Science infrastructures and application platforms. While the emergence of Cloud computing as a new computing paradigm has provided new directions and opportunities for e-Science infrastructure development, it also presents some challenges. Scientific research is increasingly finding that it is difficult to handle “big data” using traditional data processing techniques. Such challenges demonstrate the need for a comprehensive analysis on using the above-mentioned informatics techniques to develop appropriate e-Science infrastructure and platforms in the context of Cloud computing. This survey paper describes recent research advances in applying informatics techniques to facilitate scientific research particularly from the Cloud computing perspective. Our particular contributions include identifying associated research challenges and opportunities, presenting lessons learned, and describing our future vision for applying Cloud computing to e-Science. We believe our research findings can help indicate the future trend of e-Science, and can inform funding and research directions in how to more appropriately employ computing technologies in scientific research. We point out the open research issues hoping to spark new development and innovation in the e-Science field.
引用
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页码:408 / 464
页数:56
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