Context-Aware ontology and web services discovery for distributed embedded real-time systems

Distributed Embedded Real-Time Systems (DERTS) consists of hundreds of interconnected devices, typically small and wirelessly-connected, which are designed to work for a long period of time. The massive interconnection of devices and the usage of heterogeneous languages, operating platforms and data...

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Bibliographic Details
Main Authors: Zeshan F., Mohamad R., Ahmad M.N., Othman M.B., Elhag A.A.M., Hussain S.A., Ahmad A., Ali A., Ashraf M., Babar I.
Other Authors: 43061643800
Format: Article
Published: Faculty of Computer Science and Information Technology 2023
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Summary:Distributed Embedded Real-Time Systems (DERTS) consists of hundreds of interconnected devices, typically small and wirelessly-connected, which are designed to work for a long period of time. The massive interconnection of devices and the usage of heterogeneous languages, operating platforms and data standards make DERTS a competitive and complex system. In addition, the DERTS program is setting a trend of moving away from centralized, high-cost products towards lower cost and high volume products. In this regard, there is nothing more natural than considering the use of Service Oriented Architecture (SOA) to assist in the development of DERTS. This is because SOA enables different devices to exchange data regardless of issues of complexity. Moreover, context-awareness, which is widely studied for DERTS, also plays an important role for effective communication among devices. Thus, to build service-based DERTS while managing the complexity, context-aware ontologies are the best solution. In this paper, we developed a context-aware ontology for DERTS which is known as ConOntDERTS. To evaluate ConOntDERTS, we used two methods. In the first method, a criteria-based ontology evaluation was used; while in the second method, a survey was conducted to show that the results produced by ConOntDERTS were almost the same as human perception. Results of the evaluation show the consistency and feasibility of our ontology and the statistical test results show that ConOntDERTS ontology can produce consistent results with human perception. � 2019, Faculty of Computer Science and Information Technology.