Cloud Data Storage Federation for Scientific Applications
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| Publication date | 2014 |
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| Book title | Euro-Par 2013: Parallel Processing Workshops |
| Book subtitle | BigDataCloud, DIHC, FedICI, HeteroPar, HiBB, LSDVE, MHPC, OMHI, PADABS, PROPER, Resilience, ROME, and UCHPC 2013, Aachen, Germany, August 26-27, 2013 : revised selected papers |
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| ISBN (electronic) |
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| Series | Lecture Notes in Computer Science |
| Event | Euro-Par / BigDataCloud 2013 |
| Pages (from-to) | 13-22 |
| Publisher | Heidelberg: Springer |
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| Abstract |
Nowadays, data-intensive scientific research needs storage capabilities that enable efficient data sharing. This is of great importance for many scientific domains such as the Virtual Physiological Human. In this paper, we introduce a solution that federates a variety of systems ranging from file servers to more sophisticated ones used in clouds or grids. Our solution follows a client-centric approach that loosely couples a variety of data resources that may use different technologies such as Openstack-Swift, iRODS, GridFTP, and may be geographically distributed. It is implemented as a lightweight service which does not require installation of a software on the resources it uses. In this way we are able to efficiently use heterogeneous storage resources, reduce the usage complexity of multiple storage resources, and avoid vendor lock-in in case of cloud storage. To demonstrate the usability of our approach we performed a number of experiments that assess the performance and functionality of the developed system.
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| Document type | Conference contribution |
| Language | English |
| Published at | https://doi.org/10.1007/978-3-642-54420-0_2 |
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