@conference{kapsalis_kdir_2015,
author = "Kapsalis, Andreas and Kasnesis, Panagiotis and Panagiotis C. Theofanopoulos and Gkonis, Panagiotis and Christos Lavranos and Kaklamani, Dimitra I. and Venieris, Iakovos S. and George Kyriacou",
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.",
booktitle = "In Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2015)",
doi = "10.5220/0005615503880393",
isbn = "978-989-758-158-8",
keywords = "Cloud Computing, IaaS, Machine Learning, Resource Allocation",
month = "November",
pages = "388 - 393",
title = "{A} {C}loud {P}latform for {C}lassification and {R}esource {M}anagement of {C}omplex {E}lectromagnetic {P}roble",
volume = "1 - KDIR",
year = "2015",
}