Combining lyapunov optimization with actor-critic networks for privacy-aware IIoT computation offloading
G Wu, X Chen, Y Shen, Z Xu, H Zhang… - IEEE Internet of …, 2024 - ieeexplore.ieee.org
Opportunistic computation offloading is an effective way to improve the computing
performance of Industrial Internet of Things (IIoT) devices. However, as more and more …
performance of Industrial Internet of Things (IIoT) devices. However, as more and more …
CRAS-FL: Clustered resource-aware scheme for federated learning in vehicular networks
As a promising distributed learning paradigm, Federated Learning (FL) is expected to meet
the ever-increasing needs of Machine Learning (ML) based applications in Intelligent …
the ever-increasing needs of Machine Learning (ML) based applications in Intelligent …
FedAPT: Joint Adaptive Parameter Freezing and Resource Allocation for Communication-Efficient Federated Vehicular Networks
Telematics technology development offers vehicles a range of intelligent and convenient
functions, including navigation and mapping services, intelligent driving assistance, and …
functions, including navigation and mapping services, intelligent driving assistance, and …
Opportunistic routing for mobile edge computing: A community detected and task priority aware approach
As the 5G era develops quickly, there has been a significant growth in the amount of network
data. Concurrently, traditional routing algorithms are encountering growing challenges …
data. Concurrently, traditional routing algorithms are encountering growing challenges …
FeDRL-D2D: Federated Deep Reinforcement Learning-Empowered Resource Allocation Scheme for Energy Efficiency Maximization in D2D-Assisted 6G Networks
Device-to-device (D2D)-assisted 6G networks are expected to support the proliferation of
ubiquitous mobile applications by enhancing system capacity and overall energy efficiency …
ubiquitous mobile applications by enhancing system capacity and overall energy efficiency …
AMbit: An Efficient Pruning Technique in Federated Learning for Edge Computing Systems
E Hammami, P Guan, A Taherkordi… - 2024 IEEE 8th …, 2024 - ieeexplore.ieee.org
The Industrial Internet of Things (IIoT) has revolutionized industrial sectors with enhanced
connectivity, data exchange, and predictive maintenance. However, it faces various …
connectivity, data exchange, and predictive maintenance. However, it faces various …
Graph Convolutional Metric Learning for Recommender Systems in Smart Cities
X Zhao, Y Hu, Y Mu, M Li, H Wang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Aiming for creating a convenient and intelligent living environment for city dwellers,
recommender systems have been used to provide consumers with personalized …
recommender systems have been used to provide consumers with personalized …
A Comparative Study of Clustering Distance Metrics for Personalized Federated Learning in Human Activity Recognition
X Wen, C Lu, R Hu, Y Geng, Y Wang… - 2024 International …, 2024 - ieeexplore.ieee.org
In Federated Learning (FL), Non-Independent and Identically Distributed (Non-IID) data
across different clients presents a significant challenge for a global model to effectively …
across different clients presents a significant challenge for a global model to effectively …