Edge intelligence in intelligent transportation systems: A survey

T Gong, L Zhu, FR Yu, T Tang - IEEE Transactions on Intelligent …, 2023 - ieeexplore.ieee.org
Edge intelligence (EI) is becoming one of the research hotspots among researchers, which
is believed to help empower intelligent transportation systems (ITS). ITS generates a large …

Federated learning-empowered mobile network management for 5G and beyond networks: From access to core

J Lee, F Solat, TY Kim, HV Poor - … Communications Surveys & …, 2024 - ieeexplore.ieee.org
The fifth generation (5G) and beyond wireless networks are envisioned to provide an
integrated communication and computing platform that will enable multipurpose and …

A survey of blockchain and intelligent networking for the metaverse

Y Fu, C Li, FR Yu, TH Luan, P Zhao… - IEEE Internet of Things …, 2022 - ieeexplore.ieee.org
The virtual world created by the development of the Internet, computers, artificial intelligence
(AI), and hardware technologies have brought various degrees of digital transformation to …

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 …

Heterogeneous computation and resource allocation for wireless powered federated edge learning systems

J Feng, W Zhang, Q Pei, J Wu… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Federated learning (FL) is a popular edge learning approach that utilizes local data and
computing resources of network edge devices to train machine learning (ML) models while …

QoE fairness resource allocation in digital twin-enabled wireless virtual reality systems

J Feng, L Liu, X Hou, Q Pei, C Wu - IEEE journal on selected …, 2023 - ieeexplore.ieee.org
Wireless virtual reality (VR) is expected to be a technology that revolutionizes human
interaction and perceived media, where the quality of experience (QoE) is an important …

Hierarchical federated learning with quantization: Convergence analysis and system design

L Liu, J Zhang, S Song… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Federated learning (FL) is a powerful distributed machine learning framework where a
server aggregates models trained by different clients without accessing their private data …

HiFlash: Communication-efficient hierarchical federated learning with adaptive staleness control and heterogeneity-aware client-edge association

Q Wu, X Chen, T Ouyang, Z Zhou… - … on Parallel and …, 2023 - ieeexplore.ieee.org
Federated learning (FL) is a promising paradigm that enables collaboratively learning a
shared model across massive clients while kee** the training data locally. However, for …

SmartDID: a novel privacy-preserving identity based on blockchain for IoT

J Yin, Y **ao, Q Pei, Y Ju, L Liu… - IEEE Internet of Things …, 2022 - ieeexplore.ieee.org
Internet of Things (IoT) applications have penetrated into all aspects of human life. Millions
of IoT users and devices, online services, and applications combine to create a complex and …

Reputation management for consensus mechanism in vehicular edge metaverse

L Liu, J Feng, C Wu, C Chen… - IEEE Journal on Selected …, 2023 - ieeexplore.ieee.org
Metaverse is a visually rich virtual space in which users can interact with each other. By
introducing metaverse into vehicular networks, vehicular metaverse can provide users real …