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 transpor...

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Bibliographic Details
Published in:Труды Института системного программирования РАН
Main Authors: Renzo Massobrio, Sergio Nesmachnow, Andrei Tchernykh, Arutyun Avetisyan, Gleb Radchenko
Format: Article
Language:English
Published: Russian Academy of Sciences, Ivannikov Institute for System Programming 2018-10-01
Subjects:
облачные вычисления
big data
умные города
интеллектуальные транспортные системы, большие объемы данных
Online Access:https://ispranproceedings.elpub.ru/jour/article/view/208
Description
Summary: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.
ISSN:2079-8156
2220-6426

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