Towards a Cloud Computing Paradigm for Big Data Analysis in Smart Cities
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.
Proceedings of the Institute for System Programming, vol. 28, issue 6, 2016, pp. 121-140.
ISSN 2220-6426 (Online), ISSN 2079-8156 (Print).
DOI: 10.15514/ISPRAS-2016-28(6)-9Full text of the paper in pdf (in Russian) Back to the contents of the volume