Resource scheduling in edge computing: A survey

Q Luo, S Hu, C Li, G Li, W Shi - IEEE Communications Surveys …, 2021 - ieeexplore.ieee.org
With the proliferation of the Internet of Things (IoT) and the wide penetration of wireless
networks, the surging demand for data communications and computing calls for the …

Deep reinforcement learning for autonomous internet of things: Model, applications and challenges

L Lei, Y Tan, K Zheng, S Liu, K Zhang… - … Surveys & Tutorials, 2020 - ieeexplore.ieee.org
The Internet of Things (IoT) extends the Internet connectivity into billions of IoT devices
around the world, where the IoT devices collect and share information to reflect status of the …

Mobility-aware multi-hop task offloading for autonomous driving in vehicular edge computing and networks

L Liu, M Zhao, M Yu, MA Jan, D Lan… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Vehicular Edge Computing (VEC) has gained increasing interest due to its potential to
provide low latency and reduce the load in backhaul networks. In order to meet drastically …

Deep reinforcement learning for energy-efficient computation offloading in mobile-edge computing

H Zhou, K Jiang, X Liu, X Li… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
Mobile-edge computing (MEC) has emerged as a promising computing paradigm in the 5G
architecture, which can empower user equipments (UEs) with computation and energy …

Deep reinforcement learning for task offloading in mobile edge computing systems

M Tang, VWS Wong - IEEE Transactions on Mobile Computing, 2020 - ieeexplore.ieee.org
In mobile edge computing systems, an edge node may have a high load when a large
number of mobile devices offload their tasks to it. Those offloaded tasks may experience …

Imitation learning enabled task scheduling for online vehicular edge computing

X Wang, Z Ning, S Guo, L Wang - IEEE Transactions on Mobile …, 2020 - ieeexplore.ieee.org
Vehicular edge computing (VEC) is a promising paradigm based on the Internet of vehicles
to provide computing resources for end users and relieve heavy traffic burden for cellular …

DNNOff: offloading DNN-based intelligent IoT applications in mobile edge computing

X Chen, M Li, H Zhong, Y Ma… - IEEE transactions on …, 2021 - ieeexplore.ieee.org
A deep neural network (DNN) has become increasingly popular in industrial Internet of
Things scenarios. Due to high demands on computational capability, it is hard for DNN …

Multiagent deep reinforcement learning for vehicular computation offloading in IoT

X Zhu, Y Luo, A Liu, MZA Bhuiyan… - IEEE Internet of Things …, 2020 - ieeexplore.ieee.org
The development of the Internet of Things (IoT) and intelligent vehicles brings a comfortable
environment for users. Various emerging vehicular applications using artificial intelligence …

Deep reinforcement learning based resource management for multi-access edge computing in vehicular networks

H Peng, X Shen - IEEE Transactions on Network Science and …, 2020 - ieeexplore.ieee.org
In this paper, we study joint allocation of the spectrum, computing, and storing resources in a
multi-access edge computing (MEC)-based vehicular network. To support different vehicular …

Priority-aware task offloading in vehicular fog computing based on deep reinforcement learning

J Shi, J Du, J Wang, J Wang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Vehicular fog computing (VFC) has been expected as a promising scheme that can increase
the computational capability of vehicles without relying on servers. Comparing with …