1.3k citations · 2.3k across the 35 of their papers we have counts for
9 papers · 1 filter
Learning Decentralized Traffic Signal Controllers with Multi-Agent Graph Reinforcement Learning
Yao Zhang, Zhiwen Yu, Jun Zhang +4
This paper considers optimal traffic signal control in smart cities, which has been taken as a complex networked system control problem. Given the interacting dynamics among traffi…
Imperfect Digital Twin Assisted Low Cost Reinforcement Training for Multi-UAV Networks
Xiucheng Wang, Nan Cheng, Longfei Ma +3
Deep Reinforcement Learning (DRL) is widely used to optimize the performance of multi-UAV networks. However, the training of DRL relies on the frequent interactions between the UAV…
Label-free Deep Learning Driven Secure Access Selection in Space-Air-Ground Integrated Networks
Zhaowei Wang, Zhisheng Yin, Xiucheng Wang +3
In Space-air-ground integrated networks (SAGIN), the inherent openness and extensive broadcast coverage expose these networks to significant eavesdropping threats. Considering the…
Scalable Resource Management for Dynamic MEC: An Unsupervised Link-Output Graph Neural Network Approach
Xiucheng Wang, Nan Cheng, Lianhao Fu +5
Deep learning has been successfully adopted in mobile edge computing (MEC) to optimize task offloading and resource allocation. However, the dynamics of edge networks raise two cha…
SEAL: A Strategy-Proof and Privacy-Preserving UAV Computation Offloading Framework
Yuntao Wang, Zhou Su, Tom H. Luan +3
Due to the limited battery and computing resource, offloading unmanned aerial vehicles (UAVs)' computation tasks to ground infrastructure, e.g., vehicles, is a fundamental framewor…
A Survey on ChatGPT: AI-Generated Contents, Challenges, and Solutions
Yuntao Wang, Yanghe Pan, Miao Yan +2
With the widespread use of large artificial intelligence (AI) models such as ChatGPT, AI-generated content (AIGC) has garnered increasing attention and is leading a paradigm shift…
Secured and Cooperative Publish/Subscribe Scheme in Autonomous Vehicular Networks
Yuntao Wang, Zhou Su, Qichao Xu +2
In order to save computing power yet enhance safety, there is a strong intention for autonomous vehicles (AVs) in future to drive collaboratively by sharing sensory data and comput…
Trade Privacy for Utility: A Learning-Based Privacy Pricing Game in Federated Learning
Yuntao Wang, Zhou Su, Yanghe Pan +4
To prevent implicit privacy disclosure in sharing gradients among data owners (DOs) under federated learning (FL), differential privacy (DP) and its variants have become a common p…
A Survey on Digital Twins: Architecture, Enabling Technologies, Security and Privacy, and Future Prospects
Yuntao Wang, Zhou Su, Shaolong Guo +3
By interacting, synchronizing, and cooperating with its physical counterpart in real time, digital twin is promised to promote an intelligent, predictive, and optimized modern city…