URLLC resource slicing and scheduling in 5G vehicular edge computing
M Hao, D Ye, S Wang, B Tan… - 2021 IEEE 93rd Vehicular …, 2021 - ieeexplore.ieee.org
The 5th generation (5G) mobile network technology is accelerating the development of
autonomous vehicles by significantly shortening the communication latency and improving …
autonomous vehicles by significantly shortening the communication latency and improving …
Joint partial offloading and resource allocation for distributed multi-access edge computing enabled vehicular network
In the foreseeable Intelligent Transportation System (ITS), Intelligent Connected Vehicles
(ICVs) will play an important role in improving travel efficiency and safety. However, it is …
(ICVs) will play an important role in improving travel efficiency and safety. However, it is …
Deep reinforcement learning-based computation offloading in vehicular networks
L Geng, H Zhao, H Liu, Y Wang… - 2021 8th IEEE …, 2021 - ieeexplore.ieee.org
With the rapid development of 5G communications and the Internet of Things (IoT), vehicular
networks have enriched people's lives with abundant applications. Since most of such …
networks have enriched people's lives with abundant applications. Since most of such …
Deadline-aware task offloading in vehicular networks using deep reinforcement learning
MK Farimani, S Karimian-Aliabadi… - Expert Systems with …, 2024 - Elsevier
Smart vehicles have a rising demand for computation resources, and recently vehicular
edge computing has been recognized as an effective solution. Edge servers deployed in …
edge computing has been recognized as an effective solution. Edge servers deployed in …
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 …
Joint Charging Scheduling and Computation Offloading in EV-Assisted Edge Computing: A Safe DRL Approach
Electric Vehicle-assisted Multi-access Edge Computing (EV-MEC) is a promising paradigm
where EVs share their computation resources at the network edge to perform intensive …
where EVs share their computation resources at the network edge to perform intensive …
QoE-based task offloading with deep reinforcement learning in edge-enabled Internet of Vehicles
In the transportation industry, task offloading services of edge-enabled Internet of Vehicles
(IoV) are expected to provide vehicles with the better Quality of Experience (QoE). However …
(IoV) are expected to provide vehicles with the better Quality of Experience (QoE). However …
EPtask: Deep reinforcement learning based energy-efficient and priority-aware task scheduling for dynamic vehicular edge computing
The increasing complexity of vehicles has led to a growing demand for in-vehicle services
that rely on multiple sensors. In the Vehicular Edge Computing (VEC) paradigm, energy …
that rely on multiple sensors. In the Vehicular Edge Computing (VEC) paradigm, energy …
UEE-Delay Balanced Online Resource Optimization for Cooperative MEC-enabled Task Offloading in Dynamic Vehicular Networks
Mobile-edge computing (MEC), pushing the centralized cloud computing, storage, and
communication capability to the edge close to vehicular terminals, is proposed as a …
communication capability to the edge close to vehicular terminals, is proposed as a …
UAV-assisted task offloading in vehicular edge computing networks
Vehicular edge computing (VEC) provides an effective task offloading paradigm by pushing
cloud resources to the vehicular network edges, eg, road side units (RSUs). However …
cloud resources to the vehicular network edges, eg, road side units (RSUs). However …