A. Kapsalis, P. Kasnesis, P. Theofanopoulos, P. Gkonis, C. Lavranos, D. Kaklamani, I. Venieris, G. Kyriacou
{"title":"A Cloud Platform for classification and resource management of complex electromagnetic problems","authors":"A. Kapsalis, P. Kasnesis, P. Theofanopoulos, P. Gkonis, C. Lavranos, D. Kaklamani, I. Venieris, G. Kyriacou","doi":"10.5220/0005615503880393","DOIUrl":null,"url":null,"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.","PeriodicalId":102743,"journal":{"name":"2015 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K)","volume":"107 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5220/0005615503880393","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
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.