Energy-Aware Blockchain and Federated Learning-Supported Vehicular Networks
IEEE Transactions on Intelligent Transportation Systems
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, we 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.
artificial intelligence, blockchain, federated learning, Unmanned aerial vehicle, unmanned ground vehicle
M. Aloqaily, I. A. Ridhawi and M. Guizani, "Energy-Aware Blockchain and Federated Learning-Supported Vehicular Networks," in IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 11, pp. 22641-22652, Nov. 2022, doi: 10.1109/TITS.2021.3103645.
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