Scientific cloud computing : improved resource provisioning, interoperability and federation
ABSTRACT: Nowadays it is difficult to find an area in science or engineering that does not rely on computing techniques. The advancements in Scientific Computing have enabled studies in areas that were otherwise impossible. Due to the large impact of the computational science in the ongoing societal...
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| Tipo de recurso: | tesis doctoral |
| Fecha de publicación: | 2016 |
| País: | España |
| Institución: | Universidad de Cantabria (UC) |
| Repositorio: | UCrea Repositorio Abierto de la Universidad de Cantabria |
| Idioma: | inglés |
| OAI Identifier: | oai:repositorio.unican.es:10902/8210 |
| Acceso en línea: | http://hdl.handle.net/10902/8210 |
| Access Level: | acceso abierto |
| Palabra clave: | Computación distribuida Computación en la nube Planificación de recursos Computación Científica Federation Interoperability Cloud Computing Scheduling Scientific Computing |
| Sumario: | ABSTRACT: Nowadays it is difficult to find an area in science or engineering that does not rely on computing techniques. The advancements in Scientific Computing have enabled studies in areas that were otherwise impossible. Due to the large impact of the computational science in the ongoing societal and scientific challenges, several computing research infrastructures have been developed and implemented during the last years, based on different consolidated paradigms, such as High Performance Computing, High Throughput Computing and Grids. Researchers now have access to unprecedented facilities that have revolutionized the way science is performed. In this context, cloud computing has been embraced as a new emerging and promising paradigm by the scientific community due to the expectations generated around clouds. However, even if it is already being used by some research communities, we cannot neglect the fact that the cloud paradigm has been modelled to satisfy the industry needs for the next generation of enterprise and web applications. Scientific applications are unique on their own, therefore they have unique requirements that the cloud model is not able to satisfy due to its origins in the corporate world. This fact does not necessarily bring the feasibility of the cloud into question, but it is needed to perform an initial study so as to evaluate where the weak points are. In this thesis this initial gap analysis is performed as a first step for collecting a set of requirements and challenges for Science Clouds. As a second step, this work will tackle some of the challenges yielded from this initial study. To this end, we consider two different but complimentary areas: the resource provisioning and federation and interoperability in clouds. |
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