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In this paper, we propose a dedicated application modeling technique that helps to establish a predictive scheduling approach to manage a dynamically reconfigurable architecture named OLLAF. OLLAF is designed to support an operating system that deals with complex embedded applications. This model will be used for a predictive scheduling based on an early estimation of our application dynamicity. A vision system of a mobile robot application has been used to validate the presented model and scheduling approach. We have demonstrated that with our modeling we can realize an efficient predictive scheduling on a robot vision application with a mean error of 6.5%.<\/jats:p>","DOI":"10.1155\/2011\/156946","type":"journal-article","created":{"date-parts":[[2011,4,14]],"date-time":"2011-04-14T15:33:51Z","timestamp":1302795231000},"page":"1-15","source":"Crossref","is-referenced-by-count":0,"title":["Dynamic Application Model for Scheduling with Uncertainty on Reconfigurable Architectures"],"prefix":"10.1155","volume":"2011","author":[{"given":"Ismail","family":"Ktata","sequence":"first","affiliation":[{"name":"ETIS Laboratory, CNRS UMR8051, University of Cergy-Pontoise, ENSEA, 6 avenue du Ponceau 95014 Cergy-Pontoise, France"},{"name":"Computer & Embedded Systems Laboratory (CES), University of Sfax, ENIS, 3038 Sfax, Tunisia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fakhreddine","family":"Ghaffari","sequence":"additional","affiliation":[{"name":"ETIS Laboratory, CNRS UMR8051, 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