Map-Reduce for Processing GPS Data from Public Transport in Montevideo, Uruguay

This article addresses the problem of processing large volumes of historical GPS data from buses to compute quality-of-service metrics for urban transportation systems. We designed and implemented a solution to distribute the data processing on multiple processing units in a distributed computing in...

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Detalles Bibliográficos
Autores principales: Massobrio, Renzo, Pías, Andrés, Vázquez, Nicolás, Nesmachnow, Sergio
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2016
Materias:
Ciencias Informáticas
map-reduce
big data
intelligent transportation systems
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/56810
http://45jaiio.sadio.org.ar/sites/default/files/AGRANDA-01.pdf
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-56810
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
map-reduce
big data
intelligent transportation systems
spellingShingle Ciencias Informáticas
map-reduce
big data
intelligent transportation systems
Massobrio, Renzo
Pías, Andrés
Vázquez, Nicolás
Nesmachnow, Sergio
Map-Reduce for Processing GPS Data from Public Transport in Montevideo, Uruguay
topic_facet Ciencias Informáticas
map-reduce
big data
intelligent transportation systems
description This article addresses the problem of processing large volumes of historical GPS data from buses to compute quality-of-service metrics for urban transportation systems. We designed and implemented a solution to distribute the data processing on multiple processing units in a distributed computing infrastructure. For the experimental analysis we used historical data from Montevideo, Uruguay. The proposed solution scales properly when processing large volumes of input data, achieving a speedup of up to 22× when using 24 computing resources. As case studies, we used the historical data to compute the average speed of bus lines in Montevideo and identify troublesome locations, according to the delay and deviation of the times to reach each bus stop. Similar studies can be used by control authorities and policy makers to get an insight of the transportation system and improve the quality of service.
format Objeto de conferencia
Objeto de conferencia
author Massobrio, Renzo
Pías, Andrés
Vázquez, Nicolás
Nesmachnow, Sergio
author_facet Massobrio, Renzo
Pías, Andrés
Vázquez, Nicolás
Nesmachnow, Sergio
author_sort Massobrio, Renzo
title Map-Reduce for Processing GPS Data from Public Transport in Montevideo, Uruguay
title_short Map-Reduce for Processing GPS Data from Public Transport in Montevideo, Uruguay
title_full Map-Reduce for Processing GPS Data from Public Transport in Montevideo, Uruguay
title_fullStr Map-Reduce for Processing GPS Data from Public Transport in Montevideo, Uruguay
title_full_unstemmed Map-Reduce for Processing GPS Data from Public Transport in Montevideo, Uruguay
title_sort map-reduce for processing gps data from public transport in montevideo, uruguay
publishDate 2016
url http://sedici.unlp.edu.ar/handle/10915/56810
http://45jaiio.sadio.org.ar/sites/default/files/AGRANDA-01.pdf
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AT piasandres mapreduceforprocessinggpsdatafrompublictransportinmontevideouruguay
AT vazqueznicolas mapreduceforprocessinggpsdatafrompublictransportinmontevideouruguay
AT nesmachnowsergio mapreduceforprocessinggpsdatafrompublictransportinmontevideouruguay
bdutipo_str Repositorios
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