Benchmarking real-time vehicle data streaming models for a smart city

The information systems of smart cities offer project developers, institutions, industry and experts the possibility to handle massive incoming data from diverse information sources in order to produce new information services for citizens. Much of this information has to be processed as it arrives...

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Detalles Bibliográficos
Autores: Fernández Rodríguez, Jorge Yago, Álvarez García, Juan Antonio, Arias Fisteus, Jesús, Rodríguez Luaces, Miguel Ángel, Corcoba Magaña, Victor
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2017
País:España
Institución:Universidad de Sevilla (US)
Repositorio:idUS. Depósito de Investigación de la Universidad de Sevilla
OAI Identifier:oai:idus.us.es:11441/125692
Acceso en línea:https://hdl.handle.net/11441/125692
https://doi.org/10.1016/j.is.2017.09.002
Access Level:acceso abierto
Palabra clave:Smart city
Data streaming
Big Data
Distributed systems
Simulator
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spelling Benchmarking real-time vehicle data streaming models for a smart cityFernández Rodríguez, Jorge YagoÁlvarez García, Juan AntonioArias Fisteus, JesúsRodríguez Luaces, Miguel ÁngelCorcoba Magaña, VictorSmart cityData streamingBig DataDistributed systemsSimulatorThe information systems of smart cities offer project developers, institutions, industry and experts the possibility to handle massive incoming data from diverse information sources in order to produce new information services for citizens. Much of this information has to be processed as it arrives because a real-time response is often needed. Stream processing architectures solve this kind of problems, but sometimes it is not easy to benchmark the load capacity or the efficiency of a proposed architecture. This work presents a real case project in which an infrastructure was needed for gathering information from drivers in a big city, analyzing that information and sending real-time recommendations to improve driving efficiency and safety on roads. The challenge was to support the real-time recommendation ser- vice in a city with thousands of simultaneous drivers at the lowest possible cost. In addition, in order to estimate the ability of an infrastructure to handle load, a simulator that emulates the data produced by a given amount of simultaneous drivers was also developed. Experiments with the simulator show how recent stream processing platforms like Apache Kafka could replace custom-made streaming servers in a smart city to achieve a higher scalability and faster responses, together with cost reductionMinisterio de Economía y Competitividad TIN2013-46801-C4-2-RMinisterio de Economía y Competitividad TIN2013-46801-C4-1-RMInisterio de Economía y Competitividad TIN2013-46801-C4-3-RElsevierLenguajes y Sistemas InformáticosTIC134: Sistemas InformáticosMinisterio de Economía y Competitividad (MINECO). España2017info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttps://hdl.handle.net/11441/125692https://doi.org/10.1016/j.is.2017.09.002reponame:idUS. Depósito de Investigación de la Universidad de Sevillainstname:Universidad de Sevilla (US)InglésInformation Systems, 72 (December 2017), 62-76.TIN2013-46801-C4-2-RTIN2013-46801-C4-1-RTIN2013-46801-C4-3-Rhttps://www.sciencedirect.com/science/article/pii/S0306437917301916info:eu-repo/semantics/openAccessoai:idus.us.es:11441/1256922026-06-17T12:51:07Z
dc.title.none.fl_str_mv Benchmarking real-time vehicle data streaming models for a smart city
title Benchmarking real-time vehicle data streaming models for a smart city
spellingShingle Benchmarking real-time vehicle data streaming models for a smart city
Fernández Rodríguez, Jorge Yago
Smart city
Data streaming
Big Data
Distributed systems
Simulator
title_short Benchmarking real-time vehicle data streaming models for a smart city
title_full Benchmarking real-time vehicle data streaming models for a smart city
title_fullStr Benchmarking real-time vehicle data streaming models for a smart city
title_full_unstemmed Benchmarking real-time vehicle data streaming models for a smart city
title_sort Benchmarking real-time vehicle data streaming models for a smart city
dc.creator.none.fl_str_mv Fernández Rodríguez, Jorge Yago
Álvarez García, Juan Antonio
Arias Fisteus, Jesús
Rodríguez Luaces, Miguel Ángel
Corcoba Magaña, Victor
author Fernández Rodríguez, Jorge Yago
author_facet Fernández Rodríguez, Jorge Yago
Álvarez García, Juan Antonio
Arias Fisteus, Jesús
Rodríguez Luaces, Miguel Ángel
Corcoba Magaña, Victor
author_role author
author2 Álvarez García, Juan Antonio
Arias Fisteus, Jesús
Rodríguez Luaces, Miguel Ángel
Corcoba Magaña, Victor
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Lenguajes y Sistemas Informáticos
TIC134: Sistemas Informáticos
Ministerio de Economía y Competitividad (MINECO). España
dc.subject.none.fl_str_mv Smart city
Data streaming
Big Data
Distributed systems
Simulator
topic Smart city
Data streaming
Big Data
Distributed systems
Simulator
description The information systems of smart cities offer project developers, institutions, industry and experts the possibility to handle massive incoming data from diverse information sources in order to produce new information services for citizens. Much of this information has to be processed as it arrives because a real-time response is often needed. Stream processing architectures solve this kind of problems, but sometimes it is not easy to benchmark the load capacity or the efficiency of a proposed architecture. This work presents a real case project in which an infrastructure was needed for gathering information from drivers in a big city, analyzing that information and sending real-time recommendations to improve driving efficiency and safety on roads. The challenge was to support the real-time recommendation ser- vice in a city with thousands of simultaneous drivers at the lowest possible cost. In addition, in order to estimate the ability of an infrastructure to handle load, a simulator that emulates the data produced by a given amount of simultaneous drivers was also developed. Experiments with the simulator show how recent stream processing platforms like Apache Kafka could replace custom-made streaming servers in a smart city to achieve a higher scalability and faster responses, together with cost reduction
publishDate 2017
dc.date.none.fl_str_mv 2017
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/11441/125692
https://doi.org/10.1016/j.is.2017.09.002
url https://hdl.handle.net/11441/125692
https://doi.org/10.1016/j.is.2017.09.002
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Information Systems, 72 (December 2017), 62-76.
TIN2013-46801-C4-2-R
TIN2013-46801-C4-1-R
TIN2013-46801-C4-3-R
https://www.sciencedirect.com/science/article/pii/S0306437917301916
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:idUS. Depósito de Investigación de la Universidad de Sevilla
instname:Universidad de Sevilla (US)
instname_str Universidad de Sevilla (US)
reponame_str idUS. Depósito de Investigación de la Universidad de Sevilla
collection idUS. Depósito de Investigación de la Universidad de Sevilla
repository.name.fl_str_mv
repository.mail.fl_str_mv
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