2021 IEEE International Conference on Big Data (Big Data), Год журнала: 2024, Номер unknown, С. 4921 - 4929
Опубликована: Дек. 15, 2024
Язык: Английский
2021 IEEE International Conference on Big Data (Big Data), Год журнала: 2024, Номер unknown, С. 4921 - 4929
Опубликована: Дек. 15, 2024
Язык: Английский
Communications in computer and information science, Год журнала: 2025, Номер unknown, С. 3 - 22
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
0Software & Systems Modeling, Год журнала: 2024, Номер unknown
Опубликована: Ноя. 1, 2024
Язык: Английский
Процитировано
1ACM Transactions on Software Engineering and Methodology, Год журнала: 2024, Номер unknown
Опубликована: Дек. 14, 2024
Testing healthcare Internet of Things (IoT) applications at system and integration levels necessitates integrating numerous medical devices. Challenges incorporating devices are: (i) their continuous evolution, making it infeasible to include all device variants, (ii) rigorous testing scale requires multiple which is time-intensive, costly, impractical. Our collaborator, Oslo City’s health department, faced these challenges in developing automated test infrastructure, our research aims address. In this context, we propose a meta-learning-based approach (MeDeT) generate digital twins (DTs) adapt DTs evolving We evaluate MeDeT context using five widely-used integrated with real-world IoT application. evaluation assesses MeDeT’s ability across various versions different few-shot methods, the fidelity DTs, scalability operating 1000 concurrently, associated time costs. Results show that can over 96% fidelity, newer reduced cost (around one minute), operate scalable manner while maintaining level, thus serving place physical for testing.
Язык: Английский
Процитировано
02021 IEEE International Conference on Big Data (Big Data), Год журнала: 2024, Номер unknown, С. 4921 - 4929
Опубликована: Дек. 15, 2024
Язык: Английский
Процитировано
0