Organization of Smart City Services Based on Microservice Architecture
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Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-51097-7_3
Reference8 articles.
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)
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)
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
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)
5. Rafiq, A., Ping, 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)
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