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Context-aware dynamic discovery and configuration of ‘things’ in smart environments

Perera, Charith ORCID: https://orcid.org/0000-0002-0190-3346, Jayaraman, Prem Prakash, Zaslavsky, Arkady, Christen, Peter and Georgakopoulos, Dimitrios 2014. Context-aware dynamic discovery and configuration of ‘things’ in smart environments. Bessis, Nik and Dobre, Ciprian, eds. Big Data and Internet of Things: A Roadmap for Smart Environments, Vol. 546. Studies in Computational Intelligence, Springer International Publishing, pp. 215-241. (10.1007/978-3-319-05029-4_9)

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Abstract

The Internet of Things (IoT) is a dynamic global information network consisting of Internet-connected objects, such as RFIDs, sensors, actuators, as well as other instruments and smart appliances that are becoming an integral component of the future Internet. Currently, such Internet-connected objects or ‘things’ outnumber both people and computers connected to the Internet and their population is expected to grow to 50 billion in the next 5–10 years. To be able to develop IoT applications, such ‘things’ must become dynamically integrated into emerging information networks supported by architecturally scalable and economically feasible Internet service delivery models, such as cloud computing. Achieving such integration through discovery and configuration of ‘things’ is a challenging task. Towards this end, we propose a Context-Aware Dynamic Discovery of Things (CADDOT) model. We have developed a tool SmartLink, that is capable of discovering sensors deployed in a particular location despite their heterogeneity. SmartLink helps to establish the direct communication between sensor hardware and cloud-based IoT middleware platforms. We address the challenge of heterogeneity using a plug in architecture. Our prototype tool is developed on an Android platform. Further, we employ the Global Sensor Network (GSN) as the IoT middleware for the proof of concept validation. The significance of the proposed solution is validated using a test-bed that comprises 52 Arduino-based Libelium sensors.

Item Type: Book Section
Date Type: Published Online
Status: Published
Schools: Computer Science & Informatics
Subjects: Q Science > QA Mathematics > QA76 Computer software
Publisher: Springer International Publishing
ISBN: 9783319050287
Last Modified: 07 Nov 2022 10:57
URI: https://orca.cardiff.ac.uk/id/eprint/134057

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