Resource scheduling in edge computing: A survey

Q Luo, S Hu, C Li, G Li, W Shi - IEEE Communications Surveys …, 2021 - ieeexplore.ieee.org
With the proliferation of the Internet of Things (IoT) and the wide penetration of wireless
networks, the surging demand for data communications and computing calls for the …

Convergence of edge computing and deep learning: A comprehensive survey

X Wang, Y Han, VCM Leung, D Niyato… - … Surveys & Tutorials, 2020 - ieeexplore.ieee.org
Ubiquitous sensors and smart devices from factories and communities are generating
massive amounts of data, and ever-increasing computing power is driving the core of …

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 …

Blockchain empowered asynchronous federated learning for secure data sharing in internet of vehicles

Y Lu, X Huang, K Zhang, S Maharjan… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
In Internet of Vehicles (IoV), data sharing among vehicles for collaborative analysis can
improve the driving experience and service quality. However, the bandwidth, security and …

Asynchronous deep reinforcement learning for collaborative task computing and on-demand resource allocation in vehicular edge computing

L Liu, J Feng, X Mu, Q Pei, D Lan… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Vehicular Edge Computing (VEC) is enjoying a surge in research interest due to the
remarkable potential to reduce response delay and alleviate bandwidth pressure. Facing the …

A survey on the computation offloading approaches in mobile edge computing: A machine learning-based perspective

A Shakarami, M Ghobaei-Arani, A Shahidinejad - Computer Networks, 2020 - Elsevier
With the rapid developments in emerging mobile technologies, utilizing resource-hungry
mobile applications such as media processing, online Gaming, Augmented Reality (AR) …

Efficient and privacy-enhanced federated learning for industrial artificial intelligence

M Hao, H Li, X Luo, G Xu, H Yang… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
By leveraging deep learning-based technologies, industrial artificial intelligence (IAI) has
been applied to solve various industrial challenging problems in Industry 4.0. However, for …

A survey on task offloading in multi-access edge computing

A Islam, A Debnath, M Ghose, S Chakraborty - Journal of Systems …, 2021 - Elsevier
With the advent of new technologies in both hardware and software, we are in the need of a
new type of application that requires huge computation power and minimal delay …

Reducing offloading latency for digital twin edge networks in 6G

W Sun, H Zhang, R Wang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
6G is envisioned to empower wireless communication and computation through the
digitalization and connectivity of everything, by establishing a digital representation of the …

Vehicular edge computing and networking: A survey

L Liu, C Chen, Q Pei, S Maharjan, Y Zhang - Mobile networks and …, 2021 - Springer
As one key enabler of Intelligent Transportation System (ITS), Vehicular Ad Hoc Network
(VANET) has received remarkable interest from academia and industry. The emerging …