Edge computing with artificial intelligence: A machine learning perspective

H Hua, Y Li, T Wang, N Dong, W Li, J Cao - ACM Computing Surveys, 2023 - dl.acm.org
Recent years have witnessed the widespread popularity of Internet of things (IoT). By
providing sufficient data for model training and inference, IoT has promoted the development …

Computation offloading in mobile edge computing networks: A survey

C Feng, P Han, X Zhang, B Yang, Y Liu… - Journal of Network and …, 2022 - Elsevier
Computation offloading is one of the key technologies in Mobile Edge Computing (MEC),
which makes up for the deficiencies of mobile devices in terms of storage resource …

A novel secured multi-access edge computing based vanet with neuro fuzzy systems based blockchain framework

M Poongodi, S Bourouis, AN Ahmed… - Computer …, 2022 - Elsevier
In vehicle ad-hoc networks, the progression of wireless communication technology to 6G,
overcomes storage, processing, privacy, and power limits to create an efficient and …

UAV-assisted task offloading in vehicular edge computing networks

X Dai, Z Xiao, H Jiang, JCS Lui - IEEE Transactions on Mobile …, 2023 - ieeexplore.ieee.org
Vehicular edge computing (VEC) provides an effective task offloading paradigm by pushing
cloud resources to the vehicular network edges, eg, road side units (RSUs). However …

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 …

Artificial intelligence for edge service optimization in internet of vehicles: A survey

X Xu, H Li, W Xu, Z Liu, L Yao… - Tsinghua Science and …, 2021 - ieeexplore.ieee.org
The Internet of Vehicles (IoV) plays a crucial role in providing diversified services because of
its powerful capability of collecting real-time information. Generally, collected information is …

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 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 …

MEC-assisted immersive VR video streaming over terahertz wireless networks: A deep reinforcement learning approach

J Du, FR Yu, G Lu, J Wang, J Jiang… - IEEE Internet of Things …, 2020 - ieeexplore.ieee.org
Immersive virtual reality (VR) video is becoming increasingly popular owing to its enhanced
immersive experience. To enjoy ultrahigh resolution immersive VR video with wireless user …

Intelligent delay-aware partial computing task offloading for multiuser industrial Internet of Things through edge computing

X Deng, J Yin, P Guan, NN Xiong… - IEEE Internet of …, 2021 - ieeexplore.ieee.org
The development of Industrial Internet of Things (IIoT) and Industry 4.0 has completely
changed the traditional manufacturing industry. Intelligent IIoT technology usually involves a …