Federated learning for internet of things: A comprehensive survey
The Internet of Things (IoT) is penetrating many facets of our daily life with the proliferation of
intelligent services and applications empowered by artificial intelligence (AI). Traditionally …
intelligent services and applications empowered by artificial intelligence (AI). Traditionally …
Vehicular edge computing: Architecture, resource management, security, and challenges
Vehicular Edge Computing (VEC), based on the Edge Computing motivation and
fundamentals, is a promising technology supporting Intelligent Transport Systems services …
fundamentals, is a promising technology supporting Intelligent Transport Systems services …
Perception task offloading with collaborative computation for autonomous driving
Autonomous driving has so far received numerous attention from academia and industry.
However, the inevitable occlusion is a great menace to safety and reliable driving. Existing …
However, the inevitable occlusion is a great menace to safety and reliable driving. Existing …
RL/DRL meets vehicular task offloading using edge and vehicular cloudlet: A survey
The last two decades have seen a clear trend toward crafting intelligent vehicles based on
the significant advances in communication and computing paradigms, which provide a safer …
the significant advances in communication and computing paradigms, which provide a safer …
Hierarchical aerial computing for Internet of Things via cooperation of HAPs and UAVs
With the explosive increment of computation requirements, the multiaccess edge computing
(MEC) paradigm appears as an effective mechanism. Besides, as for the Internet of Things …
(MEC) paradigm appears as an effective mechanism. Besides, as for the Internet of Things …
Joint task offloading and resource allocation for vehicular edge computing based on V2I and V2V modes
W Fan, Y Su, J Liu, S Li, W Huang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
In an internet of vehicle (IoV) scenario, vehicular edge computing (VEC) exploits the
computing capabilities of the vehicles and roadside unit (RSU) to enhance the task …
computing capabilities of the vehicles and roadside unit (RSU) to enhance the task …
Deep reinforcement learning-based energy-efficient edge computing for internet of vehicles
Mobile network operators (MNOs) allocate computing and caching resources for mobile
users by deploying a central control system. Existing studies mainly use programming and …
users by deploying a central control system. Existing studies mainly use programming and …
Level-5 autonomous driving—are we there yet? a review of research literature
Autonomous vehicles are revolutionizing transport and next-generation autonomous
mobility. Such vehicles are promising to increase road safety, improve traffic efficiency …
mobility. Such vehicles are promising to increase road safety, improve traffic efficiency …
Edge intelligence for autonomous driving in 6G wireless system: Design challenges and solutions
In a level-5 autonomous driving system, the autonomous driving vehicles (AVs) are
expected to sense the surroundings via analyzing a large amount of data captured by a …
expected to sense the surroundings via analyzing a large amount of data captured by a …
Offloading optimization in edge computing for deep-learning-enabled target tracking by internet of UAVs
The empowering unmanned aerial vehicles (UAVs) have been extensively used in providing
intelligence such as target tracking. In our field experiments, a pretrained convolutional …
intelligence such as target tracking. In our field experiments, a pretrained convolutional …