Joint Self-Organizing Maps and Knowledge-Distillation-Based Communication-Efficient Federated Learning for Resource-Constrained UAV-IoT Systems

Author:

Gad Gad1ORCID,Farrag Aya2,Aboulfotouh Ahmed2ORCID,Bedda Khaled2,Fadlullah Zubair Md.1ORCID,Fouda Mostafa M.3ORCID

Affiliation:

1. Department of Computer Science, Western University, London, ON, Canada

2. Department of Computer Science, Lakehead University, Thunder Bay, ON, Canada

3. Department of Electrical and Computer Engineering, College of Science and Engineering, Idaho State University, Pocatello, ID, USA

Funder

New Frontiers in Research Fund (NFRF) Explore

Natural Sciences and Engineering Research Council of Canada under Discovery

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A dynamic analysis of UAV -based IoT networks for efficient communication using falcon optimization approach;Computers and Electrical Engineering;2024-11

2. A contemporary survey of recent advances in federated learning: Taxonomies, applications, and challenges;Internet of Things;2024-10

3. UAV Communication for Various Learning Approaches in Metaverse Healthcare Analysis Using Cloud Computing;Advances in Medical Technologies and Clinical Practice;2024-08-06

4. A Robust Federated Learning Approach for Combating Attacks Against IoT Systems Under Non-IID Challenges;2024 International Conference on Smart Applications, Communications and Networking (SmartNets);2024-05-28

5. Combating Malware Traffic in Emerging Networks: A Collaborative Learning Approach;2024 International Conference on Smart Applications, Communications and Networking (SmartNets);2024-05-28

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