Scalable Artificial Intelligence Models Integrated into Microservices Architecture Over Decentralized Digital Infrastructure for Smart City Applications
Keywords:
Smart Cities, Microservices, Artificial Intelligence, Decentralized Infrastructure, Edge Computing, Scalable Models, IoT, Cloud ArchitectureAbstract
This paper explores the integration of scalable artificial intelligence (AI) models into microservices-based architectures supported by decentralized digital infrastructure, aimed at enhancing smart city applications. By leveraging modular design principles and edge-to-cloud computing paradigms, the proposed framework addresses the limitations of monolithic AI deployment in dynamic urban environments. In the 2018 context, where smart cities were rapidly evolving yet still reliant on siloed IT architectures, this approach promotes elasticity, fault tolerance, and efficient data-driven service delivery. We analyze architectural strategies, propose a reference implementation technologies and trends that laid the foundation for such integration.
References
Khan, S., Paul, D., & Momtahan, P. (2018). Artificial intelligence framework for smart city microgrids: State of the art, challenges, and opportunities. IEEE, 1–6. https://ieeexplore.ieee.org/document/8364080
Felstaine, E., & Hermoni, O. (2018). Machine Learning, Containers, Cloud Natives, and Microservices. In Artificial Intelligence for Autonomous Networks. Taylor & Francis.
Simpkin, C., Taylor, I., Bent, G. A., & De Mel, G. (2017). Decentralized microservice workflows for coalition environments. IEEE Intelligent Systems, 32(5), 71–77. https://ieeexplore.ieee.org/document/8397424
Taherizadeh, S., Stankovski, V., & Grobelnik, M. (2018). A capillary computing architecture for dynamic IoT: Orchestration of microservices. Sensors, 18(9), 2938. https://www.mdpi.com/1424-8220/18/9/2938
Vu, T. H., Dai, N. H. B., Khanh, H. N. T., & Quang, D. N. V. (2018). Overall Structural System Solution for Supporting Services and Tourists Management in Smart Cities. ACM, 9(4), 178–183. https://dl.acm.org/doi/abs/10.1145/3287921.3287966
Power, A., & Kotonya, G. (2018). A microservices architecture for fault tolerance in IoT systems. IEEE, 1–8. https://ieeexplore.ieee.org/document/8449789
Gummadi, V. P. K. (2019). Microservices architecture with APIs: Design, implementation, and MuleSoft integration. Journal of Electrical Systems, 15(4), 130–134. https://doi.org/10.52783/jes.9328
Santos, J., Wauters, T., Volckaert, B., & De Turck, F. (2017). Fog computing for orchestration of smart city apps. Entropy, 20(1), 4. https://www.mdpi.com/1099-4300/20/1/4
Clement, S. J., McKee, D. W., & Xu, J. (2017). Service-oriented reference architecture for smart cities. IEEE, 1–6. https://ieeexplore.ieee.org/document/7943295
Gharaibeh, A., & Salahuddin, M. A. (2017). Smart Cities: A Survey on Data Management. IEEE Communications Surveys & Tutorials, 19(4), 2456–2500. https://ieeexplore.ieee.org/document/8003273
Pan, Y., Tian, Y., Liu, X., Gu, D., & Hua, G. (2016). Urban big data and smart city development. Engineering, 2(2), 196–203. https://www.sciencedirect.com/science/article/pii/S2095809916309456.
