SummaryCloud computing has permeated into the IT industry in the last few years, and it is nowadays emerging in scientific environments. Science user communities are demanding a broad range of computing power to satisfy high-performance applications needs, such as local clusters, High Performance Computing (HPC) systems and computing grids. Different workloads need from different computational models, and the cloud is already considered as a promising paradigm.The scheduling and allocation of resources is always a challenging matter in any form of computation and clouds are not an exception. Science applications have unique features that differentiate their workloads, hence their requirements have to be taken into consideration to be fulfilled when building a Science Cloud. This paper will discuss what are the main scheduling and resource allocation challenges for any Infrastructure as a Service IaaS provider supporting scientific applications.
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