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


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详细

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.

作者简介

R. Massobrio

Universidad de la Republica

编辑信件的主要联系方式.
Email: renzom@fing.edu.uy
乌拉圭, Montevideo, 11200

S. Nesmachnow

Universidad de la Republica

Email: renzom@fing.edu.uy
乌拉圭, Montevideo, 11200

A. Tchernykh

CICESE Research Center, Carretera Tijuana-Ensenada 3918; Institute for System Programming of the RAS; South Ural State University; Moscow Institute of Physics and Technology

Email: renzom@fing.edu.uy
墨西哥, Ensenada, BC, 22860; Moscow, 109004; Chelyabinsk, 454080; Dolgoprudny, Moscow oblast, 141701

A. Avetisyan

Institute for System Programming of the RAS; Lomonosov Moscow State University; Moscow Institute of Physics and Technology

Email: renzom@fing.edu.uy
俄罗斯联邦, Moscow, 109004; Moscow, 119991; Dolgoprudny, Moscow oblast, 141701

G. Radchenko

South Ural State University

Email: renzom@fing.edu.uy
俄罗斯联邦, Chelyabinsk, 454080


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