Cloud computing in e-Science: research challenges and opportunities

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 (+1 others)
<span title="2014-08-17">2014</span> <i title="Springer Nature"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/qhbautqnvzgwvm3vvdvieylhwq" style="color: black;">Journal of Supercomputing</a> </i> &nbsp;
SOA (Service Oriented Architecture), 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
more &raquo; ... a" 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.
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