Integration of IoT with cloud computing for next generation wireless technology
Author:
Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering
Link
https://link.springer.com/content/pdf/10.1007/s12243-023-01003-3.pdf
Reference6 articles.
1. Moulahi T, El Khediri S, Nayab D, Freihat M, Khan RU (2023) Effects of dataset attacks on machine learning models in e-health. Ann Telecommun. https://doi.org/10.1007/s12243-023-00951-0
2. Mekbungwan P, Lertsinsrubtavee A, Kitisin S, Pau G, Kanchanasut K (2023) Towards programmable IoT with ActiveNDN. Ann Telecommun. https://doi.org/10.1007/s12243-023-00954-x
3. Bursa SÖ, Incel ÖD, Alptekin GI (2023) Building lightweight deep learning models with TensorFlow Lite for human activity recognition on mobile devices. Ann Telecommun. https://doi.org/10.1007/s12243-023-00962-x
4. Ayache M, El Asri I, Al-Karaki JN, Bellouch M, Gawanmeh A, Tazzi K (2023) Enhanced DASS-CARE 2.0: a blockchain-based and decentralized FL framework. Ann Telecommun. https://doi.org/10.1007/s12243-023-00965-8
5. Brahimi SY, Mouffak F, Bousbaa FZ, Kerrache CA, Lagraa N, Lakas A (2023) Cloud service selection in IoFT-enabled multi-access edge computing: a game theoretic approach. Ann Telecommun. https://doi.org/10.1007/s12243-023-00950-1
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