1 citations · 2 across the 6 of their papers we have counts for
9 papers
Windowed and Quantized Group-Based ADMM for Distributed Optimization in Heterogeneous Edge Networks
Gaiguo Wei, Qingying Zhang, Heqiang Wang +2
Distributed optimization in edge networks is constrained by heterogeneous client computing capabilities and limited communication resources. We propose the Windowed and Quantized G…
P-GADMM: Parallel Group-Based ADMM for Asynchronous Optimization in Heterogeneous Edge Networks
Gaiguo Wei, Qingying Zhang, Heqiang Wang +2
The Alternating Direction Method of Multipliers (ADMM) is widely used for distributed optimization, but its synchronous implementation can suffer from efficiency loss in heterogene…
Parameter Efficient Multi-Class Intelligent Scheduling for Multimodal Online Distributed Industrial Anomaly Detection
Heqiang Wang, Weihong Yang, Zheyuan Yang +4
Industrial anomaly detection has attracted significant attention as a fundamental challenge in industrial systems. The rapid advancement of heterogeneous industrial sensors has dri…
Efficient ML-DSA Public Key Management Method with Identity for PKI and Its Application
Penghui Liu, Yi Niu, Xiaoxiong Zhong +4
With the rapid evolution of the Industrial Internet of Things (IIoT), the boundaries and scale of the Internet are continuously expanding. Consequently, the limitations of traditio…
Mitigating Modality Quantity and Quality Imbalance in Multimodal Online Federated Learning
Heqiang Wang, Weihong Yang, Xiaoxiong Zhong +3
The Internet of Things (IoT) ecosystem produces massive volumes of multimodal data from diverse sources, including sensors, cameras, and microphones. With advances in edge intellig…
Multimodal Online Federated Learning with Modality Missing in Internet of Things
Heqiang Wang, Xiang Liu, Xiaoxiong Zhong +3
The Internet of Things (IoT) ecosystem generates vast amounts of multimodal data from heterogeneous sources such as sensors, cameras, and microphones. As edge intelligence continue…
Denoising and Adaptive Online Vertical Federated Learning for Sequential Multi-Sensor Data in Industrial Internet of Things
Heqiang Wang, Xiaoxiong Zhong, Kang Liu +2
With the continuous improvement in the computational capabilities of edge devices such as intelligent sensors in the Industrial Internet of Things, these sensors are no longer limi…
Computation and Communication Efficient Lightweighting Vertical Federated Learning for Smart Building IoT
Heqiang Wang, Xiang Liu, Yucheng Liu +3
With the increasing number and enhanced capabilities of IoT devices in smart buildings, these devices are evolving beyond basic data collection and control to actively participate…
A Multi-User Effective Computation Offloading Mechanism for MEC System: Batched Multi-Armed Bandits Approach
Hangfan Li, Xiaoxiong Zhong, Xinghan Wang +2
With the development of 5G technology, mobile edge computing (MEC) is becoming a useful architecture, which is envisioned as a cloud computing extension version. Users within MEC s…