Context-Aware Service Ranking in Wireless Sensor Networks

Niu, Wenjia; Lei, Jun; Tong, Endong; Li, Gang; Chang, Liang; Shi, Zhongzhi; Ci, Song

doi:10.1007/s10922-012-9259-8

Cited by 31 publications

(9 citation statements)

References 33 publications

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“…The ranking approach is not only based on the importance of the QoS requirements, but also on users' con dence for assigning values to each QoS's attributes. [Niu et al 2014] also propose a ranking approach for WSN services using QoS with an incorporation of user feedback/rating (i.e. Quality of Experience (QoE)) for di erent services within a time interval (time threshold).…”

Section: Fig 4 Taxonomy Of Indexing Approachesmentioning

confidence: 99%

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: Fig 4 Taxonomy Of Indexing Approachesmentioning

confidence: 99%

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

2018

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“…Ao propor alguma estratégia de busca deve-se, primeiramente, delinear a estratégia de seleção, ranqueamento e recomendação. Várias abordagens são propostas [24,36,19,38,18,23,39,27,37], inclusive algumas considerando atributos de qualidade de produtores de dados, no entanto, diversas delas são complexas demais e demandam muito processamento. Assim, deseja-se que o mecanismo de busca seja rápido e exija o mínimo, ou nenhuma interação explícita.…”

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Ranqueamento de Produtores de Dados na Internet das Coisas

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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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“…In their method, user priorities are used to modify the QoS weights, and ranking score is essentially determined by the weighted sum of QoS information. The work introduced by Niu et al takes the QoS based ranking method one step further by incorporating user assessment information [28]. The authors also make use of the timeliness information (to characterise the impact of physical quality variation on QoS) to further improve ranking.…”

Section: Related Workmentioning

confidence: 99%