Deep-reinforcement-learning-based latency minimization in edge intelligence over vehicular networks
A novel paradigm that combines federated learning with blockchain to empower edge
intelligence over vehicular networks (FBVN) can enable latency-sensitive deep neural …
intelligence over vehicular networks (FBVN) can enable latency-sensitive deep neural …
[HTML][HTML] Privacy reinforcement learning for faults detection in the smart grid
Recent anticipated advancements in ad hoc Wireless Mesh Networks (WMN) have made
them strong natural candidates for Smart Grid's Neighborhood Area Network (NAN) and the …
them strong natural candidates for Smart Grid's Neighborhood Area Network (NAN) and the …
Intelligent blockchain-based edge computing via deep reinforcement learning: solutions and challenges
The convergence of mobile edge computing (MEC) and blockchain is transforming the
current computing services in wireless Internet-of-Things (IoT) networks, enabling task …
current computing services in wireless Internet-of-Things (IoT) networks, enabling task …
Secure collaborative augmented reality framework for biomedical informatics
Augmented reality is currently of interest in biomedical health informatics. At the same time,
several challenges have appeared, in particular with the rapid progress of smart sensor …
several challenges have appeared, in particular with the rapid progress of smart sensor …
Intelligent dynamic spectrum access using deep reinforcement learning for VANETs
Y Wang, X Li, P Wan, R Shao - IEEE Sensors Journal, 2021 - ieeexplore.ieee.org
In vehicular ad hoc networks (VANETs), vehicles can communicate with other vehicles or
devices through vehicle-to-X communication. However, with the rise of the Internet of Things …
devices through vehicle-to-X communication. However, with the rise of the Internet of Things …
Multi-Agent Caching Strategy for Spatial-Temporal Popularity in IoV
P He, L Cao, Y Cui, R Wang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Motivated by connected vehicles, the internet of vehicles (IoV) has a prosperous
development, thus a variety of IoV applications have emerged, which causes the dramatic …
development, thus a variety of IoV applications have emerged, which causes the dramatic …
A software-defined-networking-enabled approach for edge-cloud computing in the internet of things
The proliferation of smart devices has led to a huge amount of data streaming in the Internet
of Things (IoT). However, the resource-limited devices cannot satisfy the demands of …
of Things (IoT). However, the resource-limited devices cannot satisfy the demands of …
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 …
Consortium blockchain for cooperative location privacy preservation in 5G-enabled vehicular fog computing
A Boualouache, H Sedjelmaci… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Privacy is a key requirement for connected vehicles. Cooperation between vehicles is
mandatory for achieving location privacy preservation. However, non-cooperative vehicles …
mandatory for achieving location privacy preservation. However, non-cooperative vehicles …
Optimizing task offloading and resource allocation in edge-cloud networks: a DRL approach
Edge-cloud computing is an emerging approach in which tasks are offloaded from mobile
devices to edge or cloud servers. However, Task offloading may result in increased energy …
devices to edge or cloud servers. However, Task offloading may result in increased energy …