| Έτος: | 2015 | |||
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| Τύπος δημοσίευσης: | Συνέδριο | Λέξεις-κλειδί: | Cloud Computing, IaaS, Machine Learning, Resource Allocation | |
| Συγγραφείς: |
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| Volume: | 1 - KDIR | |||
| Book title: | In Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2015) | |||
| Pages: | 388 - 393 | |||
| Month: | November | |||
| ISBN: | 978-989-758-158-8 | |||
| Abstract: | Most scientific applications tend to have a very resource demanding nature and the simulation of such scientific problems often requires a prohibitive amount of time to complete. Distributed computing offers a solution by segmenting the application into smaller processes and allocating them to a cluster of workers. This model was widely followed by Grid Computing. However, Cloud Computing emerges as a strong alternative by offering reliable solutions for resource demanding applications and workflows that are of scientific nature. In this paper we propose a Cloud Platform that supports the simulation of complex electromagnetic problems and incorporates classification (SVM) and resource allocation (Ant Colony Optimization) methods for the effective management of these simulations. |
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