Dietmar Sommerfeld

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Many scenarios in medical research are predestined for grid computing. Large amounts of data in complex medical image, biosignal and genome processing demand large computing power and data storage. Integration of distributed, heterogeneous data, e.g. correlation between phenotype and genotype data are playing an essential part in life sciences. Sharing of(More)
In MediGRID a diverse spectrum of application scenarios from areas of bioinformatics, medical image processing, numerical simulations and clinical trials will be integrated into a Grid environment. In this paper we present the MediGRID infrastructure especially as required by medical image processing. Motivated by this selected application scenario the(More)
Infrastructure federation is becoming an increasingly important issue for modern Distributed Computing Infrastructures (DCIs): Dynamic elasticity of quasi-static Grid environments, incorporation of special-purpose resources into commoditized Cloud infrastructures, cross-community collaboration for increasingly diverging areas of modern e-Science, and Cloud(More)
—We describe four problems inherent to Grid scheduling that could be identified by means of measurements in the D-Grid. These problems make meta-scheduling nearly always a delicate task. In the face of this, we developed a new hybrid methodology to schedule application workflows which presumably supersedes existing methods. Our algorithm combines existing(More)
The MediGRID [1] project, which is part of the German e-Science initiative D-Grid, aims to provide a community Grid for researchers in the fields of bioinformatics, medical image processing, biomedical ontology, and clinical research applications. Users in the life science domain usually do not have a strong computer science background. Therefore, it is(More)