Communication-efficient federated learning for connected vehicles with constrained resources
With the upcoming next generation wireless network, vehicles are expected to be
empowered by artificial intelligence (AI). By connecting vehicles and cloud server via …
empowered by artificial intelligence (AI). By connecting vehicles and cloud server via …
Mobility, communication and computation aware federated learning for internet of vehicles
While privacy concerns entice connected and automated vehicles to incorporate on-board
federated learning (FL) solutions, an integrated vehicle-to-everything communication with …
federated learning (FL) solutions, an integrated vehicle-to-everything communication with …
VREM-FL: Mobility-Aware Computation-Scheduling Co-Design for Vehicular Federated Learning
Assisted and autonomous driving are rapidly gaining momentum, and will soon become a
reality. Among their key enablers, artificial intelligence and machine learning are expected …
reality. Among their key enablers, artificial intelligence and machine learning are expected …
Joint Accuracy and Latency Optimization for Quantized Federated Learning in Vehicular Networks
X Zhang, W Chen, H Zhao, Z Chang… - IEEE Internet of Things …, 2024 - ieeexplore.ieee.org
Nowadays, vehicular networks have emerged as a boosting technology to enhance traffic
efficiency and safety within transportation systems. As the amount of onboard data increases …
efficiency and safety within transportation systems. As the amount of onboard data increases …
A Framework of Decentralized Federated Learning With Soft Clustering and 1-Bit Compressed Sensing for Vehicular Networks
Federated Learning (FL) has been recognized as a transformative approach in vehicular
networks, enabling collaborative training between vehicles and preserving data privacy …
networks, enabling collaborative training between vehicles and preserving data privacy …
MOB-FL: Mobility-aware federated learning for intelligent connected vehicles
Federated learning (FL) is a promising approach to enable the future Internet of vehicles
consisting of intelligent connected vehicles (ICVs) with powerful sensing, computing and …
consisting of intelligent connected vehicles (ICVs) with powerful sensing, computing and …
Content-based vehicle selection and resource allocation for federated learning in IoV
S Wang, F Liu, H Xia - 2021 IEEE Wireless Communications …, 2021 - ieeexplore.ieee.org
In order to use datasets collected from multiple vehicles to train a machine learning model
while ensuring vehicle user privacy, federal learning framework was introduced into the …
while ensuring vehicle user privacy, federal learning framework was introduced into the …
Overcoming Resource Bottlenecks in Vehicular Federated Learning: A Cluster-Based and QoS-Aware Approach
Federated learning (FL) is a promising approach for processing on-board data in vehicular
networks due to its distributed nature and its ability to accurately and efficiently handle the …
networks due to its distributed nature and its ability to accurately and efficiently handle the …
Semi-asynchronous hierarchical federated learning for cooperative intelligent transportation systems
Cooperative Intelligent Transport System (C-ITS) is a promising network to provide safety,
efficiency, sustainability, and comfortable services for automated vehicles and road …
efficiency, sustainability, and comfortable services for automated vehicles and road …
IoT device friendly and communication-efficient federated learning via joint model pruning and quantization
Federated learning (FL) through its novel applications and services has enhanced its
presence as a promising tool in the Internet of Things (IoT) domain. Specifically, in a …
presence as a promising tool in the Internet of Things (IoT) domain. Specifically, in a …
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