Socialized learning: A survey of the paradigm shift for edge intelligence in networked systems

X Wang, Y Zhao, C Qiu, Q Hu… - … Surveys & Tutorials, 2024 - ieeexplore.ieee.org
Amidst the robust impetus from artificial intelligence (AI) and big data, edge intelligence (EI)
has emerged as a nascent computing paradigm, synthesizing AI with edge computing (EC) …

Location-aware and delay-minimizing task offloading in vehicular edge computing networks

Y **a, H Zhang, X Zhou, D Yuan - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Vehicular edge computing (VEC) has been reported as a new computation paradigm to
meet the low-latency requirement in vehicular networks. In this article, we study a novel …

Blockchain enabled task offloading based on edge cooperation in the digital twin vehicular edge network

C Li, Q Chen, M Chen, Z Su, Y Ding, D Lan… - Journal of Cloud …, 2023 - Springer
The rapid development of the Internet of Vehicles (IoV) along with the emergence of
intelligent applications have put forward higher requirements for massive task offloading …

Mobility and dependency-aware task offloading for intelligent assisted driving in vehicular edge computing networks

Y Li, C Yang, X Chen, Y Liu - Vehicular Communications, 2024 - Elsevier
Intelligent assisted driving is an important application in vehicular edge computing networks
(VECNs). In the intelligent transportation system (ITS), a group of moving vehicle users need …

Two-timescale joint service caching and resource allocation for task offloading with edge–cloud cooperation

Y Li, H Wang, J Sun, H Lv, W Zheng, G Feng - Computer Networks, 2024 - Elsevier
Task offloading with edge–cloud cooperation has emerged as a pivotal solution for meeting
the intricate array of application coupled with dynamically evolving business demand in 6G …

Deep Reinforcement Learning-Based Task Offloading for Vehicular Edge Computing With Flexible RSU-RSU Cooperation

W Fan, Y Zhang, G Zhou, Y Liu - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Vehicle edge computing (VEC) acts as an enhancement to provide low latency and low
energy consumption for internet of vehicles (IoV) applications. Mobility of vehicles and load …

Collaborative Edge Intelligence for Autonomous Vehicles: Opportunities and Challenges

L Bai, J Cao, M Zhang, B Li - IEEE Network, 2025 - ieeexplore.ieee.org
In this paper, we introduce collaborative edge intelligence (CEI), a novel distributed
computing paradigm, to support ultra-low latency and large-scale deployment of …

Enhancing cybersecurity and privacy protection for cloud computing-assisted vehicular network of autonomous electric vehicles: applications of machine learning

T Yang, R Sun, RS Rathore, I Baig - World Electric Vehicle Journal, 2024 - orca.cardiff.ac.uk
Due to developments in vehicle engineering and communication technologies, vehicular
networks have become an attractive and feasible solution for the future of electric …

Joint Partial Offloading and Resource Allocation for Vehicular Federated Learning Tasks

G Ma, M Hu, X Wang, H Li, Y Bian… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
In the foreseeable Intelligent Transportation System, Intelligent Connected Vehicles (ICVs)
will play an important role in improving travel efficiency and safety. However, it is …

Game theory-based vehicle selection and channel scheduling for federated learning in vehicular edge networks

T Gao, Y Ni, H Tao, Z Du, Z Zhu - Computer Networks, 2025 - Elsevier
In the last decade, Intelligent Transportation System (ITS) has benefited from the rapid
development of advanced computing and communication technology. From the perspective …