The integration of Artificial Intelligence (AI) into cloud computing and Cyber-Physical Systems (CPS) is crucial for achieving efficiency, scalability, and real-time capabilities in modern ecosystems. Containerization enhances AI deployment by improving portability, resource efficiency, and system isolation. This article addresses key design considerations and challenges in implementing containerized AI within cloud-native and CPS environments, focusing on scalability, fault tolerance, real-time responsiveness, and security. Through research analysis and case studies, it explores strategies for optimizing AI workload distribution across cloud and edge infrastructure to meet CPS demands. Future directions, including hybrid architectures and federated learning, are also discussed to support scalable, secure, and reliable AI systems for nextgeneration cloud and CPS applications.
- Pahl, C., Jamshidi, P., & Zimmermann, O. (2020). Microservices and containers. pp. 115-116. DOI: https://doi.org/10.18420/SE2020_34
- Al-Garadi, M. A., Mohamed, A., Al-Ali, A. K., Du, X., Ali, I., & Guizani, M. (2020). A survey of machine and deep learning methods for internet of things (IoT) security. IEEE communications surveys & tutorials, 22(3), 1646- 1685. DOI: https://doi.org/10.1109/COMST.2020.2988293
- Qayyum, A., Usama, M., Qadir, J., & Al-Fuqaha, A. (2020). Securing connected & autonomous vehicles: Challenges posed by adversarial machine learning and the way forward. IEEE Communications Surveys & Tutorials, 22(2), 998-1026. DOI: https://doi.org/10.1109/COMST.2020.2975048
- Cicconetti, C., Conti, M., Passarella, A., & Sabella, D. (2020). Toward distributed computing environments with serverless solutions in edge systems. IEEE Communications Magazine, 58(3), 40-46. DOI: https://doi.org/10.1109/MCOM.001.1900498
- Shi, Y., Yang, K., Jiang, T., Zhang, J., & Letaief, K. B. (2020). Communication-efficient edge AI: Algorithms and systems. IEEE Communications Surveys & Tutorials, 22(4), 2167-2191. DOI: https://doi.org/10.1109/COMST.2020.3007787
- Al-Doghman, F., Moustafa, N., Khalil, I., Sohrabi, N., Tari, Z., & Zomaya, A. Y. (2022). AI-enabled secure microservices in edge computing: Opportunities and challenges. IEEE Transactions on Services Computing, 16(2), 1485-1504. DOI: https://doi.org/10.1109/TSC.2022.3155447
- Zhang, J., Tian, J., Luo, H., Wu, S., Yin, S., & Kaynak, O. (2024). Prognostics for the Sustainability of Industrial Cyber-Physical Systems: From an Artificial Intelligence Perspective. IEEE Transactions on Industrial Cyber- Physical Systems. DOI: https://doi.org/10.1109/TICPS.2024.3433492
- Hoenig, A., Roy, K., Acquaah, Y., Yi, S., & Desai, S. (2024). Explainable AI for Cyber-Physical Systems: Issues and Challenges. IEEE Access. DOI: https://doi.org/10.1109/ACCESS.2024.3395444
- Subasi, A., Ozaltin, O., Mitra, A., Subasi, M. E., & Sarirete, A. (2023). Trustworthy artificial intelligence in healthcare. In Accelerating Strategic Changes for Digital Transformation in the Healthcare Industry (pp. 145-177). Academic Press. DOI: https://doi.org/10.1016/B978-0-443-15299-3.00015-4
- Bershchanskyi, Y., & Klym, H. (2023). Information System for Administration of Medical Institution. In 2023 13th International Conference on Dependable Systems, Services and Technologies (DESSERT) (pp. 1-4). IEEE. DOI: https://doi.org/10.1109/DESSERT61349.2023
- Al-Doghman, F., Moustafa, N., Khalil, I., Sohrabi, N., Tari, Z., & Zomaya, A. Y. (2022). AI-enabled secure microservices in edge computing: Opportunities and challenges. IEEE Transactions on Services Computing, 16(2), 1485-1504. DOI: https://doi.org/10.1109/TSC.2022.3155447