Towards a Cloud Computing Paradigm for Big Data Analysis in Smart Cities

R. Massobrio, S. Nesmachnow, A. Tchernykh, A. Avetisyan, G. Radchenko

    Research output: Contribution to journalArticlepeer-review

    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 languageEnglish
    Pages (from-to)181-189
    Number of pages9
    JournalProgram. Comput. Softw.
    Volume44
    Issue number3
    DOIs
    Publication statusPublished - 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

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