A federated learning-based edge caching approach for mobile edge computing-enabled intelligent connected vehicles
C Li, Y Zhang, Y Luo - IEEE Transactions on Intelligent …, 2022 - ieeexplore.ieee.org
Massive map data transmission and the strict demand for the privacy of high-precision maps
have brought significant challenges to the cache of high-precision maps in intelligent …
have brought significant challenges to the cache of high-precision maps in intelligent …
Mobility-aware proactive edge caching for connected vehicles using federated learning
Content Caching at the edge of vehicular networks has been considered as a promising
technology to satisfy the increasing demands of computation-intensive and latency-sensitive …
technology to satisfy the increasing demands of computation-intensive and latency-sensitive …
Mobility-aware cooperative caching in vehicular edge computing based on asynchronous federated and deep reinforcement learning
Vehicular edge computing (VEC) can learn and cache most popular contents for vehicular
users (VUs) in the roadside units (RSUs) to support real-time vehicular applications …
users (VUs) in the roadside units (RSUs) to support real-time vehicular applications …
Proactive content caching for internet-of-vehicles based on peer-to-peer federated learning
To cope with the increasing content requests from emerging vehicular applications, caching
contents at edge nodes is imperative to reduce service latency and network traffic on the …
contents at edge nodes is imperative to reduce service latency and network traffic on the …
Distributed deep multi-agent reinforcement learning for cooperative edge caching in internet-of-vehicles
Edge caching is a promising approach to reduce duplicate content transmission in Internet-
of-Vehicles (IoVs). Several Reinforcement Learning (RL) based edge caching methods have …
of-Vehicles (IoVs). Several Reinforcement Learning (RL) based edge caching methods have …
Deep reinforcement learning and permissioned blockchain for content caching in vehicular edge computing and networks
Y Dai, D Xu, K Zhang, S Maharjan… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Vehicular Edge Computing (VEC) is a promising paradigm to enable huge amount of data
and multimedia content to be cached in proximity to vehicles. However, high mobility of …
and multimedia content to be cached in proximity to vehicles. However, high mobility of …
Artificial intelligence empowered edge computing and caching for internet of vehicles
Y Dai, D Xu, S Maharjan, G Qiao… - IEEE Wireless …, 2019 - ieeexplore.ieee.org
Recent advances in edge computing and caching have significant impacts on the
developments of vehicular networks. Nevertheless, the heterogeneous requirements of on …
developments of vehicular networks. Nevertheless, the heterogeneous requirements of on …
Multi-agent reinforcement learning for cooperative edge caching in internet of vehicles
Edge caching has been emerged as a promising solution to alleviate the redundant traffic
and the content access latency in the future Internet of Vehicles (IoVs). Several …
and the content access latency in the future Internet of Vehicles (IoVs). Several …
Deep reinforcement learning for cooperative content caching in vehicular edge computing and networks
In this article, we propose a cooperative edge caching scheme, a new paradigm to jointly
optimize the content placement and content delivery in the vehicular edge computing and …
optimize the content placement and content delivery in the vehicular edge computing and …
A novel deep Q-learning-based air-assisted vehicular caching scheme for safe autonomous driving
The safety driving-related content demands of vehicle users increase rapidly, especially with
the development of autonomous driving. It is significantly necessary to obtain the safety …
the development of autonomous driving. It is significantly necessary to obtain the safety …
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