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 …

A taxonomy and survey of edge cloud computing for intelligent transportation systems and connected vehicles

P Arthurs, L Gillam, P Krause, N Wang… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
Recent advances in smart connected vehicles and Intelligent Transportation Systems (ITS)
are based upon the capture and processing of large amounts of sensor data. Modern …

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 …

EEDTO: An energy-efficient dynamic task offloading algorithm for blockchain-enabled IoT-edge-cloud orchestrated computing

H Wu, K Wolter, P Jiao, Y Deng… - IEEE Internet of Things …, 2020 - ieeexplore.ieee.org
With the proliferation of compute-intensive and delay-sensitive mobile applications, large
amounts of computational resources with stringent latency requirements are required on …

DMRO: A deep meta reinforcement learning-based task offloading framework for edge-cloud computing

G Qu, H Wu, R Li, P Jiao - IEEE Transactions on Network and …, 2021 - ieeexplore.ieee.org
With the explosive growth of mobile data and the unprecedented demand for computing
power, resource-constrained edge devices cannot effectively meet the requirements of …

Deep reinforcement learning for collaborative edge computing in vehicular networks

M Li, J Gao, L Zhao, X Shen - IEEE Transactions on Cognitive …, 2020 - ieeexplore.ieee.org
Mobile edge computing (MEC) is a promising technology to support mission-critical
vehicular applications, such as intelligent path planning and safety applications. In this …

[HTML][HTML] Machine learning technologies for secure vehicular communication in internet of vehicles: recent advances and applications

ES Ali, MK Hasan, R Hassan, RA Saeed… - Security and …, 2021 - hindawi.com
Recently, interest in Internet of Vehicles'(IoV) technologies has significantly emerged due to
the substantial development in the smart automobile industries. Internet of Vehicles' …

Scheduling IoT applications in edge and fog computing environments: a taxonomy and future directions

M Goudarzi, M Palaniswami, R Buyya - ACM Computing Surveys, 2022 - dl.acm.org
Fog computing, as a distributed paradigm, offers cloud-like services at the edge of the
network with low latency and high-access bandwidth to support a diverse range of IoT …

Ppo2: Location privacy-oriented task offloading to edge computing using reinforcement learning for intelligent autonomous transport systems

H Gao, W Huang, T Liu, Y Yin… - IEEE transactions on …, 2022 - ieeexplore.ieee.org
AI-empowered 5G/6G networks play a substantial role in taking full advantage of the Internet
of Things (IoT) to perform complex computing by offloading tasks to edge services deployed …

A gentle introduction to reinforcement learning and its application in different fields

M Naeem, STH Rizvi, A Coronato - IEEE access, 2020 - ieeexplore.ieee.org
Due to the recent progress in Deep Neural Networks, Reinforcement Learning (RL) has
become one of the most important and useful technology. It is a learning method where a …