Organization of Smart City Services Based on Microservice Architecture

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Secure Edge and Fog Computing Enabled AI for IoT and Smart Cities

Abstract

The maintenance, integration, rapid deployment, and provision of diverse services are all important directions for research on fifth-generation communication networks. This study aims to examine methods for organizing smart city services using fifth-generation networks. The methodology, data collection, analysis, and comparison of published information on how smart cities organize their services. The primary outcome of this work is identifying the most appropriate method for organizing services in fifth-generation networks. Relevance in practice. The work’s practical significance stems from the possibility of applying the major findings to the design and implementation of service architecture.

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References

  1. Muthanna, M.S.A., Wang, P., Wei, M., Rafiq, A., Josbert, N.N.: Clustering optimization of LoRa networks for perturbed ultra-dense IoT networks. Information. 12, 76 (2021)

    Article  Google Scholar 

  2. Muthanna, M.S.A., Muthanna, A., Rafiq, A., Hammoudeh, M., Alkanhel, R., Lynch, S., Abd El-Latif, A.A.: Deep reinforcement learning based transmission policy enforcement and multi-hop routing in QoS aware LoRa IoT networks. Comput. Commun. 183, 33–50 (2021)

    Article  Google Scholar 

  3. Muthanna, M.S.A., Wang, P., Wei, M., Abuarqoub, A., Alzu’bi, A., Gull, H.: Cognitive control models of multiple access IoT networks using LoRa technology. Cogn. Syst. Res., 62–73 (2021) ISSN 1389-0417

    Google Scholar 

  4. Chaaf, A., Saleh Ali Muthanna, M., Muthanna, A., Alhelaly, S., Elgendy, I.A., Iliyasu, A.M., et al.: Energy-efficient relay-based void hole prevention and repair in clustered multi-AUV underwater wireless sensor network. Secur. Commun. Netw. 2021 (2021)

    Google Scholar 

  5. Rafiq, A., **, W., Min, W., Muthanna, M.S.A.: Fog assisted 6TiSCH tri-layer network architecture for adaptive scheduling and energy-efficient offloading using rank-based Q-learning in smart industries. IEEE Sensors J. 21(22), 25489–25507 (2021)

    Article  Google Scholar 

  6. Muthanna, M.S.A., Alkanhel, R., Muthanna, A., Rafiq, A., Abdullah, W.A.M.: Towards SDN-enabled, intelligent intrusion detection system for internet of things (IoT). IEEE Access. 10, 22756–22768 (2022). https://doi.org/10.1109/ACCESS.2022.3153716

    Article  Google Scholar 

  7. Ahsan, R., **, W., Min, W., Ali, M.M.S., Nkerabahizi, J.N.: Mitigation impact of energy and time delay for computation offloading in an industrial IoT environment using Levenshtein distance algorithm. Secur. Commun. Netw., 1939–0114 (2022)

    Google Scholar 

  8. Aboulola, O., Khayyat, M., Al-Harbi, B., Muthanna, M.S.A., Muthanna, A., Fasihuddin, H., Alsulami, M.H.: Multimodal feature-assisted continuous driver behavior analysis and solving for edge-enabled internet of connected vehicles using deep learning. Appl. Sci. 11, 10462 (2021)

    Article  Google Scholar 

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Acknowledgement

The research is supported by postdoc fellowship granted by the Institute of Computer Technologies and Information Security, Southern Federal University, project № P.D./22-01-KT.

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Correspondence to Mohammed Saleh Ali Muthanna .

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Muthanna, M.S.A., Elkin, D., Likhtin, S., Muthanna, A. (2024). Organization of Smart City Services Based on Microservice Architecture. In: Abd El-Latif, A.A., Tawalbeh, L., Maleh, Y., Gupta, B.B. (eds) Secure Edge and Fog Computing Enabled AI for IoT and Smart Cities . EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-031-51097-7_3

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  • DOI: https://doi.org/10.1007/978-3-031-51097-7_3

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