Aradea, Aradea and Rianto, Rianto and Mubarok, Husni (2022) Cultivating Service Knowledge Models for IoT-Based Systems Adaptability. Informatica, An International Journal of Computing and Informatics. pp. 115-122. ISSN 1854-3871
Text
DR Aradea 2.pdf Download (245kB) |
|
Text
Cultivate.pdf Download (431kB) |
|
Text
Uji Similaritas - Cultivating Service Knowledge Models for IoT-Based Systems Adaptability.pdf Download (2MB) |
Abstract
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 selfadaptive 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. Povzetek: Model znanja o storitvah je oblikovan kot vzorec prilagajanja krmilne zanke in kontekstualno znanje za prilagodljivost različnim domenam storitev interneta stvari.
Item Type: | Article |
---|---|
Subjects: | T Technology > T Technology (General) |
Divisions: | Fakultas Teknik > Informatika > Artikel Dosen Informatika |
Depositing User: | Lelis Masridah |
Date Deposited: | 03 Nov 2022 02:27 |
Last Modified: | 12 Dec 2022 00:51 |
URI: | http://repositori.unsil.ac.id/id/eprint/7160 |
Actions (login required)
View Item |