Abstract
Biomedical analysis, in particular image and biosignal analysis, often requires several methods applied to the same data. The data is typically of large volume, so data transfer can become a bottleneck in remote analysis. Furthermore, biomedical data may contain patient data, raising data protection issues. We propose a highly virtualized infrastructure, employing Docker Swarm technology as the computing infrastructure. An underlying Openstack based IaaS cloud provides additional security features for a flexible and efficient multi-tenant analysis platform. We introduce the prototype infrastructure along a sample use-case of multiple versions of a machine-learning method applied to feature sets extracted from multidimensional biosignal recordings from Sleep Apnea patients and healthy controls.
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https://www.docker.com. If not individually referenced, details about specific Docker technologies within this paper can also be found on this website.
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Acknowledgements
The work is supported by the German Ministry of Education and Research (Project BB-IT-Boost, 03FH0061X5) and the German Ministry of Economic Affairs and Energy (ZIM Project BeCRF, Grant number KF3470401BZ4).
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Jansen, C., Witt, M., Krefting, D. (2016). Employing Docker Swarm on OpenStack for Biomedical Analysis. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2016. ICCSA 2016. Lecture Notes in Computer Science(), vol 9787. Springer, Cham. https://doi.org/10.1007/978-3-319-42108-7_23
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DOI: https://doi.org/10.1007/978-3-319-42108-7_23
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