Containerized Artificial Intelligent System Design in Cloud and Cyber-Physical Systems

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dc.citation.epage157
dc.citation.issue2
dc.citation.journalTitleДосягнення у кіберфізичних системах
dc.citation.spage151
dc.citation.volume9
dc.contributor.affiliationLviv Polytechnic National University
dc.contributor.affiliationDataArt
dc.contributor.authorBershchanskyi, Yevhen
dc.contributor.authorKlym, Halyna
dc.contributor.authorShevchuk, Yurii
dc.coverage.placenameЛьвів
dc.coverage.placenameLviv
dc.date.accessioned2025-11-06T08:48:06Z
dc.date.created2024-02-27
dc.date.issued2024-02-27
dc.description.abstractThe 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 next-generation cloud and CPS applications.
dc.format.extent151-157
dc.format.pages7
dc.identifier.citationBershchanskyi Y. Containerized Artificial Intelligent System Design in Cloud and Cyber-Physical Systems / Yevhen Bershchanskyi, Halyna Klym, Yurii Shevchuk // Advances in Cyber-Physical Systems. — Lviv : Lviv Politechnic Publishing House, 2024. — Vol 9. — No 2. — P. 151–157.
dc.identifier.citationenBershchanskyi Y. Containerized Artificial Intelligent System Design in Cloud and Cyber-Physical Systems / Yevhen Bershchanskyi, Halyna Klym, Yurii Shevchuk // Advances in Cyber-Physical Systems. — Lviv : Lviv Politechnic Publishing House, 2024. — Vol 9. — No 2. — P. 151–157.
dc.identifier.doidoi.org/10.23939/acps2024.02.151
dc.identifier.urihttps://ena.lpnu.ua/handle/ntb/117374
dc.language.isoen
dc.publisherВидавництво Львівської політехніки
dc.publisherLviv Politechnic Publishing House
dc.relation.ispartofДосягнення у кіберфізичних системах, 2 (9), 2024
dc.relation.ispartofAdvances in Cyber-Physical Systems, 2 (9), 2024
dc.relation.references[1] Pahl, C., Jamshidi, P., & Zimmermann, O. (2020). Microservices and containers, pp. 115–116. DOI: https://doi.org/10.18420/SE2020_34
dc.relation.references[2] 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
dc.relation.references[3] 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
dc.relation.references[4] 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
dc.relation.references[5] 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
dc.relation.references[6] 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
dc.relation.references[7] 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
dc.relation.references[8] 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
dc.relation.references[9] 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
dc.relation.references[10] 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/DESSERT61349.2023.10416537
dc.relation.references[11] 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
dc.relation.referencesen[1] Pahl, C., Jamshidi, P., & Zimmermann, O. (2020). Microservices and containers, pp. 115–116. DOI: https://doi.org/10.18420/SE2020_34
dc.relation.referencesen[2] 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
dc.relation.referencesen[3] 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
dc.relation.referencesen[4] 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
dc.relation.referencesen[5] 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
dc.relation.referencesen[6] 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
dc.relation.referencesen[7] 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
dc.relation.referencesen[8] 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
dc.relation.referencesen[9] 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
dc.relation.referencesen[10] 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/DESSERT61349.2023.10416537
dc.relation.referencesen[11] 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
dc.relation.urihttps://doi.org/10.18420/SE2020_34
dc.relation.urihttps://doi.org/10.1109/COMST.2020.2988293
dc.relation.urihttps://doi.org/10.1109/COMST.2020.2975048
dc.relation.urihttps://doi.org/10.1109/MCOM.001.1900498
dc.relation.urihttps://doi.org/10.1109/COMST.2020.3007787
dc.relation.urihttps://doi.org/10.1109/TSC.2022.3155447
dc.relation.urihttps://doi.org/10.1109/TICPS.2024.3433492
dc.relation.urihttps://doi.org/10.1109/ACCESS.2024.3395444
dc.relation.urihttps://doi.org/10.1016/B978-0-443-15299-3.00015-4
dc.relation.urihttps://doi.org/10.1109/DESSERT61349.2023.10416537
dc.rights.holder© Національний університет “Львівська політехніка”, 2024
dc.rights.holder© Bershchanskyi Y., Klym H., Shevchuk Yu., 2024
dc.subjectCloud Containers
dc.subjectAI Model Containerization
dc.subjectCPS
dc.subjectAI Systems
dc.subjectCloud-Native AI Design
dc.titleContainerized Artificial Intelligent System Design in Cloud and Cyber-Physical Systems
dc.typeArticle

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Advances In Cyber-Physical Systems. – 2024. – Vol. 9, No. 2