Towards a Cloud Computing Paradigm for Big Data Analysis in Smart Cities |
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| Authors: | R Massobrio S Nesmachnow A Tchernykh G Radchenko |
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| Affiliation: | 1.Universidad de la Republica,Montevideo,Uruguay;2.CICESE Research Center, Carretera Tijuana-Ensenada 3918,Fraccionamiento Zona Playitas,Ensenada,Mexico;3.Institute for System Programming of the RAS,Moscow,Russia;4.South Ural State University,Chelyabinsk,Russia;5.Lomonosov Moscow State University,Moscow,Russia;6.Moscow Institute of Physics and Technology,Dolgoprudny, Moscow oblast,Russia |
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| Abstract: | In this paper, we present a Big Data analysis paradigm related to smart cities using cloud computing infrastructures. The proposed architecture follows the MapReduce parallel model implemented using the Hadoop framework. We analyse two case studies: a quality-of-service assessment of public transportation system using historical bus location data, and a passenger-mobility estimation using ticket sales data from smartcards. Both case studies use real data from the transportation system of Montevideo, Uruguay. The experimental evaluation demonstrates that the proposed model allows processing large volumes of data efficiently. |
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