Xunzheng Zhang
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Author Swipe
View article: Multi-objective Optimization for SFC Placement in Dynamic Cross-Domain Networks
Multi-objective Optimization for SFC Placement in Dynamic Cross-Domain Networks Open
View article: Multi-objective Optimization for SFC Placement in Dynamic Cross-Domain Networks
Multi-objective Optimization for SFC Placement in Dynamic Cross-Domain Networks Open
View article: Cross-Domain Low Latency E2E Network Service Delivery with Federated and Transfer Learning
Cross-Domain Low Latency E2E Network Service Delivery with Federated and Transfer Learning Open
View article: Federated Intelligent Service Function Chain Orchestration in Future 6G Networks
Federated Intelligent Service Function Chain Orchestration in Future 6G Networks Open
View article: kubeFlower: A privacy-preserving framework for Kubernetes-based federated learning in cloud–edge environments
kubeFlower: A privacy-preserving framework for Kubernetes-based federated learning in cloud–edge environments Open
Federated Learning (FL) enables collaborative model training across edge devices while preserving data locally. Deploying FL faces challenges due to device heterogeneity. Using cloud technologies like Kubernetes (K8s) can offer computation…
View article: Table of Contents
Table of Contents Open
View article: Federated Analytics for 6G Networks: Applications, Challenges, and Opportunities
Federated Analytics for 6G Networks: Applications, Challenges, and Opportunities Open
Extensive research is underway to meet the hyper-connectivity demands of 6G networks, driven by applications like XR/VR and holographic communications, which generate substantial data requiring network-based processing, transmission, and a…
View article: Federated Analytics for 6G Networks: Applications, Challenges, and Opportunities
Federated Analytics for 6G Networks: Applications, Challenges, and Opportunities Open
Extensive research is underway to meet the hyper-connectivity demands of 6G networks, driven by applications like XR/VR and holographic communications, which generate substantial data requiring network-based processing, transmission, and a…
View article: Federated Analytics With Data Augmentation in Domain Generalization Toward Future Networks
Federated Analytics With Data Augmentation in Domain Generalization Toward Future Networks Open
Federated Domain Generalization (FDG) aims to train a global model that generalizes well to new clients in a privacy-conscious manner, even when domain shifts are encountered. The increasing concerns of knowledge generalization and data pr…
View article: Federated Hyperparameter Optimisation with Flower and Optuna
Federated Hyperparameter Optimisation with Flower and Optuna Open
Federated learning (FL) is an emerging distributed machine learning technique in which multiple clients collaborate to learn a model under the management of a central server.An FL system depends on a set of initial conditions (i.e., hyperp…