BARGAIN-MATCH: A game theoretical approach for resource allocation and task offloading in vehicular edge computing networks

Z Sun, G Sun, Y Liu, J Wang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Vehicular edge computing (VEC) is emerging as a promising architecture of vehicular
networks (VNs) by deploying the cloud computing resources at the edge of the VNs …

Computation offloading techniques in edge computing: A systematic review based on energy, QoS and authentication

Kanupriya, I Chana, RK Goyal - Concurrency and Computation …, 2024 - Wiley Online Library
In today's era, Internet of Things (IoT) devices generate a vast amount of data, which is
typically stored in the cloud environment and can be accessed by edge and IoT devices. The …

Multi-agent learning-based optimal task offloading and UAV trajectory planning for AGIN-power IoT

P Qin, Y Fu, Y **e, K Wu, X Zhang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
UAV-based air-ground integrated computing networks (AGIN) have gained significant
traction in remote areas for the Power Internet of Things (PIoT). This paper considers an …

Content service oriented resource allocation for space–air–ground integrated 6G networks: A three-sided cyclic matching approach

P Qin, M Wang, X Zhao, S Geng - IEEE Internet of Things …, 2022 - ieeexplore.ieee.org
Since the existing terrestrial fifth generation (5G) network has limited coverage, it is difficult
to meet the growing demand for seamless network connection. Meanwhile, current network …

Joint trajectory plan and resource allocation for UAV-enabled C-NOMA in air-ground integrated 6G heterogeneous network

P Qin, X Wu, Z Cai, X Zhao, Y Fu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Leveraging unmanned aerial vehicles (UAVs) for access and high altitude platform stations
(HAPSs) for data backhaul to construct the Air-Ground Integrated Network (AGIN), is a …

Quantum deep reinforcement learning for dynamic resource allocation in mobile edge computing-based IoT systems

JA Ansere, E Gyamfi, V Sharma, H Shin… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
This paper exploits a quantum-empowered machine learning algorithm to enhance
computation learning speed. We leverage quantum phenomena such as superposition and …

DRL-based resource allocation and trajectory planning for NOMA-enabled multi-UAV collaborative caching 6G network

P Qin, Y Fu, J Zhang, S Geng, J Liu… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Aerialplatform-based network has been invoked as an appealing assistance for terrestrial
cellular networks. Caching at edge UAVs is an effective emerging solution for relieving the …

DRL connects Lyapunov in delay and stability optimization for offloading proactive sensing tasks of RSUs

W Zhao, K Shi, Z Liu, X Wu, X Zheng… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
The integration of Roadside Units (RSUs) is vital for the development of autonomous driving
technologies. Challenges arise from sinking computing capabilities into RSUs and vehicles …

Dynamic parallel multi-server selection and allocation in collaborative edge computing

C Xu, J Guo, Y Li, H Zou, W Jia… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Collaborative Mobile Edge Computing (MEC) has emerged as a promising approach to
provide low service latency for computation-intensive Internet of Things applications …

Learning-based multi-UAV assisted data acquisition and computation for information freshness in WPT enabled space-air-ground PIoT

J Liu, X Zhao, P Qin, S Geng, Z Chen… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
The explosion of information data in the power Internet of Things (PIoT) poses difficulties for
data acquisition and computation of power devices located in remote areas with limited …