Attention-aware resource allocation and QoE analysis for metaverse xURLLC services

H Du, J Liu, D Niyato, J Kang, Z Xiong… - IEEE Journal on …, 2023 - ieeexplore.ieee.org
Metaverse encapsulates our expectations of the next-generation Internet, while bringing
new key performance indicators (KPIs). Although conventional ultra-reliable and low-latency …

Blockchain-empowered federated learning for healthcare Metaverses: User-centric incentive mechanism with optimal data freshness

J Kang, J Wen, D Ye, B Lai, T Wu… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Given the revolutionary role of metaverses, healthcare metaverses are emerging as a
transformative force, creating intelligent healthcare systems that offer immersive and …

Connectivity-aware contract for incentivizing iot devices in complex wireless blockchain

W Wang, J Chen, Y Jiao, J Kang… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
Blockchain is considered the critical backbone technology for secure and trusted Internet of
Things (IoT) in the future 6G network. However, deploying a blockchain system in a complex …

Electric Vehicle Aggregation in a PV-Battery Charging Station: A Contract-Based Approach

G Li, J Yang, F Wu, X Zhu, J Xu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
As the proportion of high-power fast charging piles increases, how to more stably aggregate
electric vehicles to avoid market risks brought about by user charging behavior is an urgent …

Task freshness-aware incentive mechanism for vehicle twin migration in vehicular metaverses

J Wen, J Kang, Z Xiong, Y Zhang, H Du… - 2023 IEEE …, 2023 - ieeexplore.ieee.org
Vehicular metaverse, which is treated as the future continuum between automotive industry
and metaverse, is envisioned as a blended immersive domain as the digital twins of …

Stochastic coded federated learning: Theoretical analysis and incentive mechanism design

Y Sun, J Shao, Y Mao, S Li… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Federated learning (FL) has achieved great success as a privacy-preserving distributed
training paradigm, where many edge devices collaboratively train a machine learning model …

Heterogeneous differential-private federated learning: Trading privacy for utility truthfully

X Lin, J Wu, J Li, C Sang, S Hu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Differential-private federated learning (DP-FL) has emerged to prevent privacy leakage
when disclosing encoded sensitive information in model parameters. However, the existing …

3C Resource Sharing for Personalized Content Delivery in B5G Networks: A Contract Approach

B Qian, T Ma, K Yu, Y Xu, Y Wu… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
With the emergence of numerous new applications and the explosive growth of Internet of
Things (IoT) devices in beyond 5G (B5G) networks, the massive yet delay-sensitive …

Qos based contract design for profit maximization in iot-enabled data markets

J Chen, J Farooq, Q Zhu - IEEE Internet of Things Journal, 2023 - ieeexplore.ieee.org
The massive deployment of Internet of Things (IoT) devices, including sensors and
actuators, is ushering in smart and connected communities of the future. The massive …

Collaborative honeypot defense in uav networks: A learning-based game approach

Y Wang, Z Su, A Benslimane, Q Xu… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
The proliferation of unmanned aerial vehicles (UAVs) opens up new opportunities for on-
demand service provision anywhere and anytime, but also exposes UAVs to a variety of …