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 …

Mobility-aware multi-hop task offloading for autonomous driving in vehicular edge computing and networks

L Liu, M Zhao, M Yu, MA Jan, D Lan… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Vehicular Edge Computing (VEC) has gained increasing interest due to its potential to
provide low latency and reduce the load in backhaul networks. In order to meet drastically …

Survey on digital twin edge networks (DITEN) toward 6G

F Tang, X Chen, TK Rodrigues… - IEEE Open Journal of …, 2022 - ieeexplore.ieee.org
The next generation (6G) wireless systems aim to cater to the Internet of Everything (IoE)
and revolutionize customer services and applications to a fully intelligent and autonomous …

[HTML][HTML] A comprehensive survey on reinforcement-learning-based computation offloading techniques in Edge Computing Systems

D Hortelano, I de Miguel, RJD Barroso… - Journal of Network and …, 2023 - Elsevier
In recent years, the number of embedded computing devices connected to the Internet has
exponentially increased. At the same time, new applications are becoming more complex …

Digital twin assisted task offloading for aerial edge computing and networks

B Li, Y Liu, L Tan, H Pan… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Considering the user mobility and unpredictable mobile edge computing (MEC)
environments, this paper studies the intelligent task offloading problem in unmanned aerial …

Dynamic admission control and resource allocation for mobile edge computing enabled small cell network

J Huang, B Lv, Y Wu, Y Chen… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Mobile edge computing (MEC) has recently risen as a promising paradigm to meet the
increasing resource requirements of the terminal devices. Meanwhile, small cell network …

Adaptive digital twin for vehicular edge computing and networks

Y Dai, Y Zhang - Journal of Communications and Information …, 2022 - ieeexplore.ieee.org
To better support the emerging vehicular applications and multimedia services, vehicular
edge computing (VEC) provides computing and caching services in proximity to vehicles, by …

Cooperative federated learning and model update verification in blockchain-empowered digital twin edge networks

L Jiang, H Zheng, H Tian, S Xie… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
With the rapid development of Internet of Things (IoT), the digital twin is emerging as one of
the most promising technologies to connect physical components with digital space for …

A QoS-aware technique for computation offloading in IoT-edge platforms using a convolutional neural network and Markov decision process

A Heidari, MAJ Jamali, NJ Navimipour… - IT …, 2023 - ieeexplore.ieee.org
Offloading is one of the critical enablers of the Internet of Things (IoT) as it helps overcome
the resource limitations of individual objects. Offering enough computational power for IoT …

Federated multi-agent deep reinforcement learning for resource allocation of vehicle-to-vehicle communications

X Li, L Lu, W Ni, A Jamalipour… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Dynamic topology, fast-changing channels and the time sensitivity of safety-related services
present challenges to the status quo of resource allocation for cellular-underlaying vehicle …