Energy-Aware Blockchain and Federated Learning-Supported Vehicular Networks
The aerial capabilities and flexibility in movement of Unmanned Aerial Vehicles (UAVs) has enabled them to adaptively provide both traditional and more contemporary services. In this article, the authors introduce a solution that integrates the capabilities of both UAVs and Unmanned Ground Vehicles (UGVs) to provide both intelligent connectivity and services to both aerial and ground connected devices. A cooperative solution is adopted that considers nodes’ power and movement constraints. The UAV and UGV cooperative process ensures continuous power availability to UAVs to support seamless and continuous service availability to end-devices. A Federated Learning (FL) approach is adopted at the edge to ensure accurate and up-to-date service provisioning in accordance with the surrounding environment and network constraints. Moreover, Blockchain technology is used to decentralize the provisioning and control aspects, and ensure authenticity and integrity. Extensive simulations are conducted to test the soundness and applicability of the proposed solution. Results show significant improvement in terms of connectivity, service availability, and UAV energy enhancements when compared to traditional mobile and vehicular communication techniques.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/oclc/41297384
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Supplemental Notes:
- Copyright © 2022, IEEE.
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Authors:
- Aloqaily, Moayad
- Al Ridhawi, Ismaeel
- Guizani, Mohsen
- Publication Date: 2022-11
Language
- English
Media Info
- Media Type: Web
- Features: References;
- Pagination: pp 22641-22652
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Serial:
- IEEE Transactions on Intelligent Transportation Systems
- Volume: 23
- Issue Number: 11
- Publisher: Institute of Electrical and Electronics Engineers (IEEE)
- ISSN: 1524-9050
- Serial URL: http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6979
Subject/Index Terms
- TRT Terms: Blockchains; Connected vehicles; Drones; Energy consumption; Machine learning; Mobile robots; Network nodes
- Subject Areas: Aviation; Data and Information Technology; Energy; Highways; Vehicles and Equipment;
Filing Info
- Accession Number: 01876342
- Record Type: Publication
- Files: TRIS
- Created Date: Mar 21 2023 9:27AM