Stud Health Technol Inform
October 2010
Grid technologies are appealing to deal with the challenges raised by computational neurosciences and support multi-centric brain studies. However, core grids middleware hardly cope with the complex neuroimaging data representation and multi-layer data federation needs. Moreover, legacy neuroscience environments need to be preserved and cannot be simply superseded by grid services.
View Article and Find Full Text PDFThe NeuroLOG project designs an ambitious neurosciences middleware, gaining from many existing components and learning from past project experiences. It is targeting a focused application area and adopting a user-centric perspective to meet the neuroscientists expectations. It aims at fostering the adoption of HealthGrids in a pre-clinical community.
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July 2005
This paper presents mu grid, a light weight middleware for grid applications, and focuses mainly on security issues--more specifically on the access control to resources--that are critical for the gridification of many medical applications. For this purpose, we use Sygn as a distributed, certificate based, and flexible access control mechanism, which has been fully integrated in mu grid. We discuss the advantages of the solution compared to classical grid approaches and the limitations of the final architecture.
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