Context-based search engine for industrial IoT: Discovery, search, selection, and usage of devices

Lunardi, Willian T.; Matos, Éverton de; Tiburski, Ramão Tiago; Amaral, Leonardo Albernaz; Marczak, Sabrina; Hessel, Fabiano

doi:10.1109/etfa.2015.7301477

Cited by 39 publications

(30 citation statements)

References 17 publications

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“…Indexing to enable query of the data published by IoT resources could be thematic (e.g. [Lunardi et al 2015]) where indexing can be constructed based on terms such as XML eld given that the data is stored in XML format. The indexing could also be built according to the spatial and temporal features of the data (e.g.…”

Section: Analysis and Discussionmentioning

confidence: 99%

“…However, this brings into view the second problem; the queries are text-based and not suitable for large volumes of numerical data. Moreover, in most of the cases, the indexing is centralised as in [Lunardi et al 2015]. Distributed approaches for indexing resources have been discussed such as [Hoseinitabatabaei et al 2014;Paganelli and Parlanti 2012].…”

Section: Analysis and Discussionmentioning

confidence: 99%

“…For example, a framework has been proposed in [Lunardi et al 2015] to allow a set of various devices to register to a middleware. The framework provides an indexing method based on selected XML elds from the meta-data description of di erent connected devices in the network.…”

Section: Thematic Datamentioning

confidence: 99%

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Large-Scale Indexing, Discovery, and Ranking for the Internet of Things (IoT)

2018

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Network-enabled sensing and actuation devices are key enablers to connect real-world objects to the cyber world. The Internet of Things (IoT) consists of the network-enabled devices and communication technologies that allow connectivity and integration of physical objects (Things) into the digital world (Internet). Enormous amounts of dynamic IoT data are collected from Internet-connected devices. IoT data is usually multi-variant streams that are heterogeneous, sporadic, multi-modal and spatio-temporal. IoT data can be disseminated with di erent granularities and have diverse structures, types and qualities. Dealing with the data deluge from heterogeneous IoT resources and services imposes new challenges on indexing, discovery and ranking mechanisms that will allow building applications that require on-line access and retrieval of ad-hoc IoT data. However, the existing IoT data indexing and discovery approaches are complex or centralised which hinders their scalability. The primary objective of this paper is to provide a holistic overview of the state-of-the-art on indexing, discovery and ranking of IoT data. The paper aims to pave the way for researchers to design, develop, implement and evaluate techniques and approaches for on-line large-scale distributed IoT applications and services.

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Section: Analysis and Discussionmentioning

confidence: 99%

Section: Analysis and Discussionmentioning

confidence: 99%

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Large-Scale Indexing, Discovery, and Ranking for the Internet of Things (IoT)

2018

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“…Já no COBASEN [21], a busca começa com a elaboração de uma query formada por palavras chave. Há uma tabela deíndice invertido que ajuda a localizar os sensores que possuem um alto grau de similaridade com a string de busca submetida.…”

Section: Trabalhos Relacionadosunclassified

“…Observa-se que das três propostas, apenas o trabalho de Perera et al [27] possui uma estratégia de busca estruturada. Os outros dois [11,21] aceitam como busca sequências de palavras chave que descrevem o fenômeno que se quer observar, detalhes de descrição dos dispositivos ou níveis de qualidade. Guinard et al [11], como foi discutido, utiliza dicionários para expandir as palavras chave.…”

Section: Trabalhos Relacionadosunclassified

Ranqueamento de Produtores de Dados na Internet das Coisas

Silva

Gama

Lóscio

2017

Anais Do Simpósio Brasileiro De Sistemas De Informação (SBSI)

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RESUMOCom a ascensão da Internet das Coisas (Internet of Things -IoT ), bilhões de dispositivos estarão conectadosà internet do futuro produzindo, consumindo e processando dados e se comunicando uns com os outros. Descobrir e selecionar de forma eficiente os dispositivos que melhor respondem a uma determinada necessidade se mostram como problemas relevantes a serem investigados no paradigma IoT. Face a este problema, o presente trabalho propôs: (i) o uso e o monitoramento dinâmico de métricas de qualidade na descrição dos produtores de dados, (ii) proposta de uma técnica de ranqueamento de produtores de dados que utilize atributos de qualidade diversos, (iii) a proposta do conceito de fila dinâmica de resultados no mecanismo de busca, visando economia de processamento e ganho de desempenho e (iv) uso do estilo arquitetural REST para a oferta dos produtores de dados como recursos. Por fim, foi considerado um cenário de uso do aplicativo móvel Bike Cidadão com o objetivo de avaliar a performance das contribuições propostas. ABSTRACTWith the rise of the Internet of Things (IoT) billion devices will be connected to the internet of the future producing, consuming and processing data and communicating with each other. Discover and select e ciently the devices best suited to a particular need, appear as relevant issues to be investigated in the IoT. In view of this problem, the present work proposes: (i) using and monitoring quality metrics in the description of the data producers, (ii) the propose of a ranking of data producers technique that makes use of quality attributes, (iii) the suggestion of dynamic queue results by the search engine and (iv) the use of REST style for providing

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Enhancing IoT Platforms for Autonomous Device Discovery and Selection

Schneider

Hirmer

2022

Service-Oriented Computing

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Context-based search engine for industrial IoT: Discovery, search, selection, and usage of devices

Cited by 39 publications

References 17 publications

Large-Scale Indexing, Discovery, and Ranking for the Internet of Things (IoT)

Large-Scale Indexing, Discovery, and Ranking for the Internet of Things (IoT)

Ranqueamento de Produtores de Dados na Internet das Coisas

Enhancing IoT Platforms for Autonomous Device Discovery and Selection

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