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A knowledge-based resource discovery for Internet of Things

Perera, Charith and Vasilakos, Athanasios V. 2016. A knowledge-based resource discovery for Internet of Things. Knowledge-Based Systems 109 , pp. 122-136. 10.1016/j.knosys.2016.06.030

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Abstract

In the sensing as a service paradigm, Internet of Things (IoT) Middleware platforms allow data consumers to retrieve the data they want without knowing the underlying technical details of IoT resources (i.e. sensors and data processing components). However, configuring an IoT middleware platform and retrieving data is a significant challenge for data consumers as it requires both technical knowledge and domain expertise. In this paper, we propose a knowledge driven approach called Context Aware Sensor Configuration Model (CASCOM) to simplify the process of configuring IoT middleware platforms, so the data consumers, specifically non-technical personnel, can easily retrieve the data they required. In this paper, we demonstrate how IoT resources can be described using semantics in such away that they can later be used to compose service work-flows. Such automated semantic-knowledge-based IoT resource composition approach advances the current research. We demonstrate the feasibility and the usability of our approach through a prototype implementation based on an IoT middleware called Global Sensor Networks (GSN), though our model can be generalized to any other middleware platform.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Subjects: Q Science > QA Mathematics > QA76 Computer software
Publisher: Elsevier
ISSN: 0950-7051
Date of First Compliant Deposit: 11 August 2020
Date of Acceptance: 26 June 2016
Last Modified: 11 Aug 2020 14:30
URI: http://orca.cf.ac.uk/id/eprint/134078

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