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This article is cited in 8 scientific papers (total in 8 papers)
Towards a cloud computing paradigm for big data analysis in smart cities
Renzo Massobrioa, Sergio Nesmachnowa, Andrei Tchernykhb, Arutyun Avetisyanc, Gleb Radchenkod a Universidad de la República
b CICESE Research Center
c Institute for System Programming of the RAS
d South Ural State University
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.
Keywords:
big data, cloud computing, smart cities, intelligent transportation systems.
Citation:
Renzo Massobrio, Sergio Nesmachnow, Andrei Tchernykh, Arutyun Avetisyan, Gleb Radchenko, “Towards a cloud computing paradigm for big data analysis in smart cities”, Proceedings of ISP RAS, 28:6 (2016), 121–140
Linking options:
https://www.mathnet.ru/eng/tisp89 https://www.mathnet.ru/eng/tisp/v28/i6/p121
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Abstract page: | 289 | Full-text PDF : | 124 | References: | 32 |
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