Cultivating Service Knowledge Models for IoT-Based Systems Adaptability

Aradea Aradea, Rianto Rianto, Husni Mubarok


Service models have been widely developed and applied to the Internet of Things (IoT) systems. However, current service models tend to emphasize the need for various types of services based on certain IoT service domains. Hence, the limitations of this service model are not prepared to meet the general objectives of IoT-based systems so that services cannot adapt to various IoT domains. Besides, developers should redefine service requirements and specifications. This paper introduces a service knowledge model, where meta-model elements are defined more generically. The control loops pattern of a self-adaptive model as a service-forming component and behavior regulator are deployed as the investigative approach. The developed service knowledge model encompasses five main classes, nine sub-classes, twelve object properties, and eighty-nine axioms. Meta-model evaluation results revealed that the level of completeness and consistency of 100% related to the structure, language, and syntax of a knowledge model. Additionally, the proposed model has an architecture adaptability index (AAI) level = 0.89. Hence, it can reduce the uncertainty of IoT services at runtime.

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