Reinforcement learning methods for computation offloading: a systematic review

Z Zabihi, AM Eftekhari Moghadam… - ACM Computing …, 2023 - dl.acm.org
Today, cloud computation offloading may not be an appropriate solution for delay-sensitive
applications due to the long distance between end-devices and remote datacenters. In …

Task co-offloading for D2D-assisted mobile edge computing in industrial internet of things

X Dai, Z **ao, H Jiang, M Alazab… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
Mobile edge computing (MEC) and device-to-device (D2D) offloading are two promising
paradigms in the industrial Internet of Things (IIoT). In this article, we investigate task co …

Reverse auction-based computation offloading and resource allocation in mobile cloud-edge computing

H Zhou, T Wu, X Chen, S He, D Guo… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
This article proposes a novel Reverse Auction-based Computation Offloading and Resource
Allocation Mechanism, named RACORAM for the mobile Cloud-Edge computing. The basic …

Machine Learning Empowered Emerging Wireless Networks in 6G: Recent Advancements, Challenges & Future Trends

HMF Noman, E Hanafi, KA Noordin, K Dimyati… - IEEE …, 2023 - ieeexplore.ieee.org
The upcoming 6G networks are sixth-sense next-generation communication networks with
an ever-increasing demand for enhanced end-to-end (E2E) connectivity towards a …

Distributed deep multi-agent reinforcement learning for cooperative edge caching in internet-of-vehicles

H Zhou, K Jiang, S He, G Min… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Edge caching is a promising approach to reduce duplicate content transmission in Internet-
of-Vehicles (IoVs). Several Reinforcement Learning (RL) based edge caching methods have …

Joint optimization of computing offloading and service caching in edge computing-based smart grid

H Zhou, Z Zhang, D Li, Z Su - IEEE Transactions on Cloud …, 2022 - ieeexplore.ieee.org
With the continuous expansion of the power Internet of Things (IoT) and the rapid increase in
the number of Smart Devices (SDs), the data generated by SDs has exponentially …

Cost minimization-oriented computation offloading and service caching in mobile cloud-edge computing: An A3C-based approach

H Zhou, Z Wang, H Zheng, S He… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
This paper considers computation offloading and service caching in a three-tier mobile
cloud-edge computing structure, in which Mobile Users (MUs) have subscribed to the Cloud …

UAV-aided computation offloading in mobile-edge computing networks: A Stackelberg game approach

H Zhou, Z Wang, G Min, H Zhang - IEEE Internet of Things …, 2022 - ieeexplore.ieee.org
Unmanned aerial vehicles (UAVs) are considered as a promising method to provide
additional computation capability and wide coverage for mobile users (MUs), especially …

Accelerating deep learning inference via model parallelism and partial computation offloading

H Zhou, M Li, N Wang, G Min… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
With the rapid development of Internet-of-Things (IoT) and the explosive advance of deep
learning, there is an urgent need to enable deep learning inference on IoT devices in Mobile …

A deep reinforcement learning-based resource management game in vehicular edge computing

X Zhu, Y Luo, A Liu, NN **ong… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Vehicular Edge Computing (VEC) is a promising paradigm that leverages the vehicles to
offload computation tasks to the nearby VEC server with the aim of supporting the low …