Learning-assisted energy minimization for MEC systems with noncompletely overlapping NOMA

S Han, B Lu, S Lin, X Hong, J Shi - IEEE Systems Journal, 2023 - ieeexplore.ieee.org
This article investigates the long-term energy minimization of mobile edge computing (MEC)
systems with multiuser noncompletely overlapping nonorthogonal multiple access (NOMA) …

Federated Double Deep Q-learning Based Computation Offloading in Mobility-Aware Vehicle Clusters

W Ye, K Zheng, Y Wang, Y Tang - IEEE Access, 2023 - ieeexplore.ieee.org
On the edge side of internet of vehicles (IoV), mobile edge computing (MEC) servers with
certain computational resources are deployed to provide computational service for vehicles …

Deadline-constrained RSU-to-vehicle task offloading scheme for vehicular fog networks

M Khabbaz - IEEE Transactions on Vehicular Technology, 2023 - ieeexplore.ieee.org
In Vehicular Fog Computing (VFC), the RSU-to-Vehicle (R2V) task offloading process is
highly affected by undesirable yet sometimes inevitable events (eg, buffer exhaustion, task …

Towards Risk-Averse Edge Computing With Deep Reinforcement Learning

D Xu, X Su, H Wang, S Tarkoma… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Recently, artificial intelligence paves the way for the development of smart services for
people anytime and anywhere, which poses great challenges on accessing computing …

A metaheuristic-based task offloading scheme with a trade-off between delay and resource utilization in IoT platform

N Kumari, PK Jana - Cluster Computing, 2023 - Springer
Fog computing has emerged as the most popular technology for processing delay-sensitive
tasks in the Internet of Things platform. However, offloading tasks to suitable fog nodes (FNs) …

Deep Reinforcement Learning Empowered Resource Allocation in Vehicular Fog Computing

L Sun, M Liu, J Guo, X Yu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Recent advances in fog computing had significantly impacted the development of the
Internet of Vehicles (IoV). Rapidly growing on-vehicle applications demand low-latency …

Task scheduling of computation-intensive graph jobs in UAV-assisted hybrid vehicular networks

J Chai, Y Meng, W Wang, Y Lyu, H Yue, X Liu - Vehicular Communications, 2023 - Elsevier
As a promising new form in mobile edge computing network, Vehicular Edge Computing
(VEC) can further improve the Quality of Service (QoS) of users. However, when edge …

Toward a Virtual Edge Service Provider: Actor-Critic Learning to Incentivize the Computation Nodes

M Cheraghinia, SH Rastegar… - … on Network Science …, 2023 - ieeexplore.ieee.org
The growing development of computation-intensive applications has considerably increased
the demand for computing resources in the network. Many of these applications require …

Cross-regional task offloading with multi-agent reinforcement learning for hierarchical vehicular fog computing

Y Hou, Z Wei, S Liu, B Li, R Zhang… - … IEEE Symposium on …, 2023 - ieeexplore.ieee.org
Vehicular fog computing (VFC) can make full use of computing resources of idle vehicles to
increase computing capability. However, most current VFC architectures only focus on the …

Divergent Selection Task Offloading Strategy for Connected Vehicles Based on Incentive Mechanism

S Yu, Y Guo, N Li, D Xue, H Yuan - Electronics, 2023 - mdpi.com
With the improvements in the intelligent level of connected vehicles (CVs), travelers can
enjoy services such as self-driving, self-parking and audiovisual entertainment inside the …