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A Generic Context-Aware Service Discovery Architecture for IoT Services

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Smart Secure Systems – IoT and Analytics Perspective (ICIIT 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 808))

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Abstract

Internet of Things (IoT) is the networks of physical objects or things that are connected to the Internet via the embedded devices to provide appropriate services to the user. These services stimulate the physical object to communicate and interact with the global environments efficiently. In the current state-of-art, with the increase in the number of services provided by the physical objects, the discovery of desirable services is a key challenge. Hence, in this work, a generic architecture for context-aware service discovery among the existing IoT services has been proposed. The context aware service discovery architecture investigates and understands the context based on the submitted users request and provides the users with the relevant information and services. In order to performs a comparison between the properties of the user request and the registered instance, this discovery architecture has been developed using the Web Ontology Language (OWL) based context-aware computing and a service oriented approach. To justify the performance of the proposed context aware solution, test scenarios and user survey has been carried out on a weather forecasting scenario to determine the relevancy retrieval ratio.

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Correspondence to S. Sasirekha .

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Sasirekha, S., Swamynathan, S., Keerthana, S. (2018). A Generic Context-Aware Service Discovery Architecture for IoT Services. In: Venkataramani, G., Sankaranarayanan, K., Mukherjee, S., Arputharaj, K., Sankara Narayanan, S. (eds) Smart Secure Systems – IoT and Analytics Perspective. ICIIT 2017. Communications in Computer and Information Science, vol 808. Springer, Singapore. https://doi.org/10.1007/978-981-10-7635-0_21

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  • DOI: https://doi.org/10.1007/978-981-10-7635-0_21

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-7634-3

  • Online ISBN: 978-981-10-7635-0

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