Joint computation offloading and resource allocation for edge-cloud collaboration in internet of vehicles via deep reinforcement learning
Mobile edge computing (MEC) and cloud computing (CC) have been considered as the key
technologies to improve the task processing efficiency for Internet of Vehicles (IoV). In this …
technologies to improve the task processing efficiency for Internet of Vehicles (IoV). In this …
Deep reinforcement learning for offloading and resource allocation in vehicle edge computing and networks
Mobile Edge Computing (MEC) is a promising technology to extend the diverse services to
the edge of Internet of Things (IoT) system. However, the static edge server deployment may …
the edge of Internet of Things (IoT) system. However, the static edge server deployment may …
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 …
environment for users. Various emerging vehicular applications using artificial intelligence …
Distributed computation offloading method based on deep reinforcement learning in ICV
With the rapid development of Intelligent Connected Vehicles (ICVs), more effective
computation resources optimization schemes in task scheduling are exactly required for …
computation resources optimization schemes in task scheduling are exactly required for …
Deep reinforcement learning for collaborative edge computing in vehicular networks
Mobile edge computing (MEC) is a promising technology to support mission-critical
vehicular applications, such as intelligent path planning and safety applications. In this …
vehicular applications, such as intelligent path planning and safety applications. In this …
Task offloading in vehicular edge computing networks via deep reinforcement learning
Given the rapid increase of various applications in vehicular networks, it is crucial to
consider a flexible architecture to improve the Quality of Service (QoS). Utilizing Multi-access …
consider a flexible architecture to improve the Quality of Service (QoS). Utilizing Multi-access …
Dynamic edge computation offloading for internet of vehicles with deep reinforcement learning
Recent developments in the Internet of Vehicles (IoV) enabled the myriad emergence of a
plethora of data-intensive and latency-sensitive vehicular applications, posing significant …
plethora of data-intensive and latency-sensitive vehicular applications, posing significant …
Com-DDPG: task offloading based on multiagent reinforcement learning for information-communication-enhanced mobile edge computing in the internet of vehicles
H Gao, X Wang, W Wei, A Al-Dulaimi… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
The emergence of the Internet of Vehicles (IoV) introduces challenges regarding
computation-intensive and time-sensitive related services for data processing and …
computation-intensive and time-sensitive related services for data processing and …
Asynchronous deep reinforcement learning for collaborative task computing and on-demand resource allocation in vehicular edge computing
Vehicular Edge Computing (VEC) is enjoying a surge in research interest due to the
remarkable potential to reduce response delay and alleviate bandwidth pressure. Facing the …
remarkable potential to reduce response delay and alleviate bandwidth pressure. Facing the …
A deep reinforcement learning based computation offloading with mobile vehicles in vehicular edge computing
Vehicular edge networks involve edge servers that are close to mobile devices to provide
extra computation resource to complete the computation tasks of mobile devices with low …
extra computation resource to complete the computation tasks of mobile devices with low …
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