Fog e edge computing : uma arquitetura híbrida em um ambiente de internet das coisas
Autor(a) principal: | |
---|---|
Data de Publicação: | 2017 |
Tipo de documento: | Dissertação |
Idioma: | por |
Título da fonte: | Biblioteca Digital de Teses e Dissertações da PUC_RS |
Texto Completo: | http://tede2.pucrs.br/tede2/handle/tede/7730 |
Resumo: | Internet of Things (IoT) is considered a computational evolution that advocates the existence of a large number of physical objects embedded with sensors and actuators, connected by wireless networks and communicating through the Internet. From the beginning of the concept to the present day, IoT is widely used in the various sectors of industry and also in academia. One of the needs encountered in these areas was to be connected to IoT devices or subsystems throughout the world. Thus, cloud computing gains space in these scenarios where there is a need to be connected and communicating with a middleware to perform the data processing of the devices. The concept of cloud computing refers to the use of memory, storage and processing of shared resources, interconnected by the Internet. However, IoT applications sensitive to communication latency, such as medical emergency applications, military applications, critical security applications, among others, are not feasible with the use of cloud computing, since for the execution of all calculations and actions messaging between devices and the cloud is required. Solving this limitation found in the use of cloud computing, the concept of fog computing arises and whose main idea is to create a federated processing layer, still in the local network of the computing devices of the ends of the network. In addition to fog computing, there is also edge computing operating directly on the devices layer, performing some kind of processing, even with little computational complexity, in order to further decrease the volume of communication, besides collaborating to provide autonomy in decision making yet in the Things layer. A major challenge for both fog and edge computing within the IoT scenario is the definition of a system architecture that can be used in different application domains, such as health, smart cities and others. This work presents a system architecture for IoT devices capable of enabling data processing in the devices themselves or the closest to them, creating the edge computing layer and fog computing layer that can be applied in different domains, improving Quality of Services (QoS) and autonomy in decision making, even if the devices are temporarily disconnected from the network (offline). The validation of this architecture was done within two application scenarios, one of public lighting in smart city environment and another simulating an intelligent agricultural greenhouse. The main objectives of the tests were to verify if the use of the concepts of edge and fog computing improve system efficiency compared to traditional IoT architectures. The tests revealed satisfactory results, improving connection times, processing and delivery of information to applications, reducing the volume of communication between devices and core middleware, and improving communications security. It also presents a review of related work in both academia and industry. |
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Hessel, Fabiano Passuelohttp://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4728802T7Amaral, Leonardo Albernazhttp://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4735703H0http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4380342Y2Schenfeld, Matheus Crespi2017-11-14T10:44:39Z2017-03-23http://tede2.pucrs.br/tede2/handle/tede/7730Internet of Things (IoT) is considered a computational evolution that advocates the existence of a large number of physical objects embedded with sensors and actuators, connected by wireless networks and communicating through the Internet. From the beginning of the concept to the present day, IoT is widely used in the various sectors of industry and also in academia. One of the needs encountered in these areas was to be connected to IoT devices or subsystems throughout the world. Thus, cloud computing gains space in these scenarios where there is a need to be connected and communicating with a middleware to perform the data processing of the devices. The concept of cloud computing refers to the use of memory, storage and processing of shared resources, interconnected by the Internet. However, IoT applications sensitive to communication latency, such as medical emergency applications, military applications, critical security applications, among others, are not feasible with the use of cloud computing, since for the execution of all calculations and actions messaging between devices and the cloud is required. Solving this limitation found in the use of cloud computing, the concept of fog computing arises and whose main idea is to create a federated processing layer, still in the local network of the computing devices of the ends of the network. In addition to fog computing, there is also edge computing operating directly on the devices layer, performing some kind of processing, even with little computational complexity, in order to further decrease the volume of communication, besides collaborating to provide autonomy in decision making yet in the Things layer. A major challenge for both fog and edge computing within the IoT scenario is the definition of a system architecture that can be used in different application domains, such as health, smart cities and others. This work presents a system architecture for IoT devices capable of enabling data processing in the devices themselves or the closest to them, creating the edge computing layer and fog computing layer that can be applied in different domains, improving Quality of Services (QoS) and autonomy in decision making, even if the devices are temporarily disconnected from the network (offline). The validation of this architecture was done within two application scenarios, one of public lighting in smart city environment and another simulating an intelligent agricultural greenhouse. The main objectives of the tests were to verify if the use of the concepts of edge and fog computing improve system efficiency compared to traditional IoT architectures. The tests revealed satisfactory results, improving connection times, processing and delivery of information to applications, reducing the volume of communication between devices and core middleware, and improving communications security. It also presents a review of related work in both academia and industry.Internet das Coisas (IoT) é considerada uma evolução computacional que preconiza a existência de uma grande quantidade de objetos físicos embarcados com sensores e atuadores, conectados por redes sem fio e que se comunicam através da Internet. Desde o surgimento do conceito até os dias atuais, a IoT é amplamente utilizada nos diversos setores da indústria e também no meio acadêmico. Uma das necessidades encontradas nessas áreas foi a de estar conectado com dispositivos ou subsistemas de IoT espalhados por todo o mundo. Assim, cloud computing ganha espaço nesses cenários, onde existe a necessidade de estar conectado e se comunicando com um middleware para realizar o processamento dos dados dos dispositivos. O conceito de cloud computing refere-se ao uso de memória, armazenamento e processamento de recursos compartilhados, interligados pela Internet. No entanto, aplicações IoT sensíveis à latência de comunicação, tais como, aplicações médico-emergenciais, aplicações militares, aplicações de segurança crítica, entre outras, são inviáveis com o uso de cloud computing, visto que para a execução de todos os cálculos e ações é necessária a troca de mensagens entre dispositivos e nuvem. Solucionando essa limitação encontrada na utilização de cloud computing, surge o conceito de fog computing, cuja ideia principal é criar uma camada federada de processamento ainda na rede local dos dispositivos de computação das extremidades da rede. Além de fog computing também surge edge computing operando diretamente na camada dos dispositivos, realizando algum tipo de processamento, mesmo que de pouca complexidade computacional, a fim de diminuir ainda mais o volume de comunicação, além de colaborar para prover autonomia na tomada de decisões ainda na camada das coisas. Um grande desafio tanto para fog quanto para edge computing dentro do cenário de IoT é a definição de uma arquitetura de sistema que possa ser usada em diferentes domínios de aplicação, como saúde, cidades inteligentes entre outros. Esse trabalho apresenta uma arquitetura de sistema para dispositivos IoT capaz de habilitar o processamento de dados nos próprios dispositivos ou o mais próximo deles, criando a camada de edge e fog computing que podem ser aplicadas em diferentes domínios, melhorando a Qualidade dos Serviços (QoS) e autonomia na tomada de decisão, mesmo se os dispositivos estiverem temporariamente desconectados da rede (offline). A validação dessa arquitetura foi feita dentro de dois cenários de aplicação, um de iluminação pública em ambiente de IoT e outro simulando uma estufa agrícola inteligente. Os principais objetivos das execuções dos testes foram verificar se a utilização dos conceitos de edge e fog computing melhoram a eficiência do sistema em comparação com arquiteturas tradicionais de IoT. Os testes revelaram resultados satisfatórios, melhorando os tempos de conexão, processamento e entrega das informações às aplicações, redução do volume de comunicação entre dispositivos e core middleware, além de melhorar a segurança nas comunicações. Também é apresentada uma revisão de trabalhos relacionados tanto no meio acadêmico como no da indústria.Submitted by Caroline Xavier (caroline.xavier@pucrs.br) on 2017-11-14T10:44:09Z No. of bitstreams: 1 DIS_MATHEUS_CRESPI_SCHENFELD_COMPLETO.pdf: 6989470 bytes, checksum: 4a16f12e8953d43da2cb18cc63c6119a (MD5)Approved for entry into archive by Caroline Xavier (caroline.xavier@pucrs.br) on 2017-11-14T10:44:28Z (GMT) No. of bitstreams: 1 DIS_MATHEUS_CRESPI_SCHENFELD_COMPLETO.pdf: 6989470 bytes, checksum: 4a16f12e8953d43da2cb18cc63c6119a (MD5)Made available in DSpace on 2017-11-14T10:44:39Z (GMT). No. of bitstreams: 1 DIS_MATHEUS_CRESPI_SCHENFELD_COMPLETO.pdf: 6989470 bytes, checksum: 4a16f12e8953d43da2cb18cc63c6119a (MD5) Previous issue date: 2017-03-23application/pdfhttp://tede2.pucrs.br:80/tede2/retrieve/170277/DIS_MATHEUS_CRESPI_SCHENFELD_COMPLETO.pdf.jpgporPontifícia Universidade Católica do Rio Grande do SulPrograma de Pós-Graduação em Ciência da ComputaçãoPUCRSBrasilFaculdade de InformáticaInternet of ThingsFog ComputingEdge ComputingMiddlewareCloud ComputingCIENCIA DA COMPUTACAO::TEORIA DA COMPUTACAOFog e edge computing : uma arquitetura híbrida em um ambiente de internet das coisasinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisTrabalho não apresenta restrição para publicação1974996533081274470500500500-3008542510401149144-862078257083325301info:eu-repo/semantics/openAccessreponame:Biblioteca Digital de Teses e Dissertações da PUC_RSinstname:Pontifícia Universidade Católica do Rio Grande do Sul (PUCRS)instacron:PUC_RSTHUMBNAILDIS_MATHEUS_CRESPI_SCHENFELD_COMPLETO.pdf.jpgDIS_MATHEUS_CRESPI_SCHENFELD_COMPLETO.pdf.jpgimage/jpeg3938http://tede2.pucrs.br/tede2/bitstream/tede/7730/4/DIS_MATHEUS_CRESPI_SCHENFELD_COMPLETO.pdf.jpgee867ca28fe6e0cf118a4f44d2203f3cMD54TEXTDIS_MATHEUS_CRESPI_SCHENFELD_COMPLETO.pdf.txtDIS_MATHEUS_CRESPI_SCHENFELD_COMPLETO.pdf.txttext/plain167285http://tede2.pucrs.br/tede2/bitstream/tede/7730/3/DIS_MATHEUS_CRESPI_SCHENFELD_COMPLETO.pdf.txtd6533d02b65d39d932b9410d30349592MD53ORIGINALDIS_MATHEUS_CRESPI_SCHENFELD_COMPLETO.pdfDIS_MATHEUS_CRESPI_SCHENFELD_COMPLETO.pdfapplication/pdf6989470http://tede2.pucrs.br/tede2/bitstream/tede/7730/2/DIS_MATHEUS_CRESPI_SCHENFELD_COMPLETO.pdf4a16f12e8953d43da2cb18cc63c6119aMD52LICENSElicense.txtlicense.txttext/plain; charset=utf-8610http://tede2.pucrs.br/tede2/bitstream/tede/7730/1/license.txt5a9d6006225b368ef605ba16b4f6d1beMD51tede/77302017-11-14 12:00:58.539oai:tede2.pucrs.br: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Biblioteca Digital de Teses e Dissertaçõeshttp://tede2.pucrs.br/tede2/PRIhttps://tede2.pucrs.br/oai/requestbiblioteca.central@pucrs.br||opendoar:2017-11-14T14:00:58Biblioteca Digital de Teses e Dissertações da PUC_RS - Pontifícia Universidade Católica do Rio Grande do Sul (PUCRS)false |
dc.title.por.fl_str_mv |
Fog e edge computing : uma arquitetura híbrida em um ambiente de internet das coisas |
title |
Fog e edge computing : uma arquitetura híbrida em um ambiente de internet das coisas |
spellingShingle |
Fog e edge computing : uma arquitetura híbrida em um ambiente de internet das coisas Schenfeld, Matheus Crespi Internet of Things Fog Computing Edge Computing Middleware Cloud Computing CIENCIA DA COMPUTACAO::TEORIA DA COMPUTACAO |
title_short |
Fog e edge computing : uma arquitetura híbrida em um ambiente de internet das coisas |
title_full |
Fog e edge computing : uma arquitetura híbrida em um ambiente de internet das coisas |
title_fullStr |
Fog e edge computing : uma arquitetura híbrida em um ambiente de internet das coisas |
title_full_unstemmed |
Fog e edge computing : uma arquitetura híbrida em um ambiente de internet das coisas |
title_sort |
Fog e edge computing : uma arquitetura híbrida em um ambiente de internet das coisas |
author |
Schenfeld, Matheus Crespi |
author_facet |
Schenfeld, Matheus Crespi |
author_role |
author |
dc.contributor.advisor1.fl_str_mv |
Hessel, Fabiano Passuelo |
dc.contributor.advisor1Lattes.fl_str_mv |
http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4728802T7 |
dc.contributor.advisor-co1.fl_str_mv |
Amaral, Leonardo Albernaz |
dc.contributor.advisor-co1Lattes.fl_str_mv |
http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4735703H0 |
dc.contributor.authorLattes.fl_str_mv |
http://buscatextual.cnpq.br/buscatextual/visualizacv.do?id=K4380342Y2 |
dc.contributor.author.fl_str_mv |
Schenfeld, Matheus Crespi |
contributor_str_mv |
Hessel, Fabiano Passuelo Amaral, Leonardo Albernaz |
dc.subject.eng.fl_str_mv |
Internet of Things Fog Computing Edge Computing Middleware Cloud Computing |
topic |
Internet of Things Fog Computing Edge Computing Middleware Cloud Computing CIENCIA DA COMPUTACAO::TEORIA DA COMPUTACAO |
dc.subject.cnpq.fl_str_mv |
CIENCIA DA COMPUTACAO::TEORIA DA COMPUTACAO |
description |
Internet of Things (IoT) is considered a computational evolution that advocates the existence of a large number of physical objects embedded with sensors and actuators, connected by wireless networks and communicating through the Internet. From the beginning of the concept to the present day, IoT is widely used in the various sectors of industry and also in academia. One of the needs encountered in these areas was to be connected to IoT devices or subsystems throughout the world. Thus, cloud computing gains space in these scenarios where there is a need to be connected and communicating with a middleware to perform the data processing of the devices. The concept of cloud computing refers to the use of memory, storage and processing of shared resources, interconnected by the Internet. However, IoT applications sensitive to communication latency, such as medical emergency applications, military applications, critical security applications, among others, are not feasible with the use of cloud computing, since for the execution of all calculations and actions messaging between devices and the cloud is required. Solving this limitation found in the use of cloud computing, the concept of fog computing arises and whose main idea is to create a federated processing layer, still in the local network of the computing devices of the ends of the network. In addition to fog computing, there is also edge computing operating directly on the devices layer, performing some kind of processing, even with little computational complexity, in order to further decrease the volume of communication, besides collaborating to provide autonomy in decision making yet in the Things layer. A major challenge for both fog and edge computing within the IoT scenario is the definition of a system architecture that can be used in different application domains, such as health, smart cities and others. This work presents a system architecture for IoT devices capable of enabling data processing in the devices themselves or the closest to them, creating the edge computing layer and fog computing layer that can be applied in different domains, improving Quality of Services (QoS) and autonomy in decision making, even if the devices are temporarily disconnected from the network (offline). The validation of this architecture was done within two application scenarios, one of public lighting in smart city environment and another simulating an intelligent agricultural greenhouse. The main objectives of the tests were to verify if the use of the concepts of edge and fog computing improve system efficiency compared to traditional IoT architectures. The tests revealed satisfactory results, improving connection times, processing and delivery of information to applications, reducing the volume of communication between devices and core middleware, and improving communications security. It also presents a review of related work in both academia and industry. |
publishDate |
2017 |
dc.date.accessioned.fl_str_mv |
2017-11-14T10:44:39Z |
dc.date.issued.fl_str_mv |
2017-03-23 |
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info:eu-repo/semantics/publishedVersion |
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info:eu-repo/semantics/masterThesis |
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masterThesis |
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http://tede2.pucrs.br/tede2/handle/tede/7730 |
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http://tede2.pucrs.br/tede2/handle/tede/7730 |
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por |
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por |
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1974996533081274470 |
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500 500 500 |
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Pontifícia Universidade Católica do Rio Grande do Sul |
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