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. © 2018, Pleiades Publishing, Ltd.
Original language | English |
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Pages (from-to) | 181-189 |
Number of pages | 9 |
Journal | Program. Comput. Softw. |
Volume | 44 |
Issue number | 3 |
DOIs | |
Publication status | Published - 2018 |
Keywords
- big data
- cloud computing
- intelligent transportation systems
- smart cities
- Cloud computing
- Data handling
- Information analysis
- Intelligent systems
- Quality of service
- Smart cards
- Smart city
- Cloud computing infrastructures
- Experimental evaluation
- Hadoop frameworks
- Intelligent transportation systems
- Mobility estimation
- Proposed architectures
- Public transportation systems
- Transportation system
- Big data