Topology-aware Federated Learning in Edge Computing: A Comprehensive Survey
Fuente:
arXiv
Saved in:
| Main Authors: | Wu, Jiajun, Drew, Steve, Dong, Fan, Zhu, Zhuangdi, Zhou, Jiayu |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
FedGreen: Carbon-aware Federated Learning with Model Size Adaptation
by: Abbasi, Ali, et al.
Published: (2024)
by: Abbasi, Ali, et al.
Published: (2024)
Navigating High-Degree Heterogeneity: Federated Learning in Aerial and Space Networks
by: Dong, Fan, et al.
Published: (2024)
by: Dong, Fan, et al.
Published: (2024)
Beyond the Federation: Topology-aware Federated Learning for Generalization to Unseen Clients
by: Ma, Mengmeng, et al.
Published: (2024)
by: Ma, Mengmeng, et al.
Published: (2024)
A Comprehensive Survey of Federated Transfer Learning: Challenges, Methods and Applications
by: Guo, Wei, et al.
Published: (2024)
by: Guo, Wei, et al.
Published: (2024)
Towards cost-effective and resource-aware aggregation at Edge for Federated Learning
by: Khan, Ahmad Faraz, et al.
Published: (2022)
by: Khan, Ahmad Faraz, et al.
Published: (2022)
Semi-decentralized Federated Time Series Prediction with Client Availability Budgets
by: Bao, Yunkai, et al.
Published: (2025)
by: Bao, Yunkai, et al.
Published: (2025)
HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems
by: Lin, Zheng, et al.
Published: (2025)
by: Lin, Zheng, et al.
Published: (2025)
A Survey on Contribution Evaluation in Vertical Federated Learning
by: Cui, Yue, et al.
Published: (2024)
by: Cui, Yue, et al.
Published: (2024)
Heterogeneity-Aware Cooperative Federated Edge Learning with Adaptive Computation and Communication Compression
by: Zhang, Zhenxiao, et al.
Published: (2024)
by: Zhang, Zhenxiao, et al.
Published: (2024)
Lumos: Heterogeneity-aware Federated Graph Learning over Decentralized Devices
by: Pan, Qiying, et al.
Published: (2023)
by: Pan, Qiying, et al.
Published: (2023)
Knowledge Distillation in Federated Learning: a Survey on Long Lasting Challenges and New Solutions
by: Qin, Laiqiao, et al.
Published: (2024)
by: Qin, Laiqiao, et al.
Published: (2024)
A Survey on Collaborative DNN Inference for Edge Intelligence
by: Ren, Weiqing, et al.
Published: (2022)
by: Ren, Weiqing, et al.
Published: (2022)
Federated Continual Learning for Edge-AI: A Comprehensive Survey
by: Wang, Zi, et al.
Published: (2024)
by: Wang, Zi, et al.
Published: (2024)
EMO: Edge Model Overlays to Scale Model Size in Federated Learning
by: Wu, Di, et al.
Published: (2025)
by: Wu, Di, et al.
Published: (2025)
Heterogeneous Tasks Offloading in Vehicular Edge Computing: A Federated Meta Deep Reinforcement Learning Approach
by: Huang, Yaorong, et al.
Published: (2026)
by: Huang, Yaorong, et al.
Published: (2026)
A Joint Approach to Local Updating and Gradient Compression for Efficient Asynchronous Federated Learning
by: Song, Jiajun, et al.
Published: (2024)
by: Song, Jiajun, et al.
Published: (2024)
Energy-Efficient Federated Learning for Edge Real-Time Vision via Joint Data, Computation, and Communication Design
by: Hou, Xiangwang, et al.
Published: (2025)
by: Hou, Xiangwang, et al.
Published: (2025)
Flame: Simplifying Topology Extension in Federated Learning
by: Daga, Harshit, et al.
Published: (2023)
by: Daga, Harshit, et al.
Published: (2023)
Lightweight Federated Learning over Wireless Edge Networks
by: Hou, Xiangwang, et al.
Published: (2025)
by: Hou, Xiangwang, et al.
Published: (2025)
FedTeddi: Temporal Drift and Divergence Aware Scheduling for Timely Federated Edge Learning
by: Bai, Yuxuan, et al.
Published: (2025)
by: Bai, Yuxuan, et al.
Published: (2025)
Training Machine Learning models at the Edge: A Survey
by: Khouas, Aymen Rayane, et al.
Published: (2024)
by: Khouas, Aymen Rayane, et al.
Published: (2024)
TASP: Topology-aware Sequence Parallelism
by: Wang, Yida, et al.
Published: (2025)
by: Wang, Yida, et al.
Published: (2025)
Federated Learning Model Aggregation in Heterogenous Aerial and Space Networks
by: Dong, Fan, et al.
Published: (2023)
by: Dong, Fan, et al.
Published: (2023)
Robust Federated Learning against Model Perturbation in Edge Networks
by: Jin, Dongzi, et al.
Published: (2025)
by: Jin, Dongzi, et al.
Published: (2025)
Agglomerative Federated Learning: Empowering Larger Model Training via End-Edge-Cloud Collaboration
by: Wu, Zhiyuan, et al.
Published: (2023)
by: Wu, Zhiyuan, et al.
Published: (2023)
Stitching Satellites to the Edge: Pervasive and Efficient Federated LEO Satellite Learning
by: Elmahallawy, Mohamed, et al.
Published: (2024)
by: Elmahallawy, Mohamed, et al.
Published: (2024)
BEFL: Balancing Energy Consumption in Federated Learning for Mobile Edge IoT
by: Ju, Zehao, et al.
Published: (2024)
by: Ju, Zehao, et al.
Published: (2024)
AirFed: A Federated Graph-Enhanced Multi-Agent Reinforcement Learning Framework for Multi-UAV Cooperative Mobile Edge Computing
by: Wang, Zhiyu, et al.
Published: (2025)
by: Wang, Zhiyu, et al.
Published: (2025)
Beyond Model Scale Limits: End-Edge-Cloud Federated Learning with Self-Rectified Knowledge Agglomeration
by: Wu, Zhiyuan, et al.
Published: (2025)
by: Wu, Zhiyuan, et al.
Published: (2025)
Computation and Communication Efficient Lightweighting Vertical Federated Learning for Smart Building IoT
by: Wang, Heqiang, et al.
Published: (2024)
by: Wang, Heqiang, et al.
Published: (2024)
Leveraging Foundation Models for Efficient Federated Learning in Resource-restricted Edge Networks
by: Atapour, S. Kawa, et al.
Published: (2024)
by: Atapour, S. Kawa, et al.
Published: (2024)
Demo: A Practical Testbed for Decentralized Federated Learning on Physical Edge Devices
by: Feng, Chao, et al.
Published: (2025)
by: Feng, Chao, et al.
Published: (2025)
A Survey on Federated Fine-tuning of Large Language Models
by: Wu, Yebo, et al.
Published: (2025)
by: Wu, Yebo, et al.
Published: (2025)
Locally Estimated Global Perturbations are Better than Local Perturbations for Federated Sharpness-aware Minimization
by: Fan, Ziqing, et al.
Published: (2024)
by: Fan, Ziqing, et al.
Published: (2024)
Heterogeneity-Aware Resource Allocation and Topology Design for Hierarchical Federated Edge Learning
by: Gao, Zhidong, et al.
Published: (2024)
by: Gao, Zhidong, et al.
Published: (2024)
Communication-Efficient Federated Learning by Quantized Variance Reduction for Heterogeneous Wireless Edge Networks
by: Wang, Shuai, et al.
Published: (2025)
by: Wang, Shuai, et al.
Published: (2025)
PFLlib: A Beginner-Friendly and Comprehensive Personalized Federated Learning Library and Benchmark
by: Zhang, Jianqing, et al.
Published: (2023)
by: Zhang, Jianqing, et al.
Published: (2023)
Overcoming Challenges of Partial Client Participation in Federated Learning : A Comprehensive Review
by: Sen, Mrinmay, et al.
Published: (2025)
by: Sen, Mrinmay, et al.
Published: (2025)
Knowledge-Driven Federated Graph Learning on Model Heterogeneity
by: Wu, Zhengyu, et al.
Published: (2025)
by: Wu, Zhengyu, et al.
Published: (2025)
Vertical Federated Learning: Challenges, Methodologies and Experiments
by: Wei, Kang, et al.
Published: (2022)
by: Wei, Kang, et al.
Published: (2022)
Similar Items
-
FedGreen: Carbon-aware Federated Learning with Model Size Adaptation
by: Abbasi, Ali, et al.
Published: (2024) -
Navigating High-Degree Heterogeneity: Federated Learning in Aerial and Space Networks
by: Dong, Fan, et al.
Published: (2024) -
Beyond the Federation: Topology-aware Federated Learning for Generalization to Unseen Clients
by: Ma, Mengmeng, et al.
Published: (2024) -
A Comprehensive Survey of Federated Transfer Learning: Challenges, Methods and Applications
by: Guo, Wei, et al.
Published: (2024) -
Towards cost-effective and resource-aware aggregation at Edge for Federated Learning
by: Khan, Ahmad Faraz, et al.
Published: (2022)