Hierarchical Federated Learning

Hierarchical Federated Learning (HFL) addresses the limitations of traditional federated learning by structuring the learning process across multiple layers, typically involving edge servers and a central server, to improve efficiency and scalability in distributed systems. Current research focuses on optimizing HFL algorithms, such as those based on gradient descent, ADMM, and Bayesian methods, to address challenges like data heterogeneity, communication overhead, and adversarial attacks, often incorporating techniques like model compression and dynamic client selection. This approach holds significant promise for enhancing privacy-preserving machine learning in diverse applications, including autonomous driving, healthcare, and IoT, by enabling collaborative model training across geographically dispersed or resource-constrained devices.

Papers

September 29, 2024

Fast-Convergent and Communication-Alleviated Heterogeneous Hierarchical Federated Learning in Autonomous Driving
Wei-Bin Kou, Qingfeng Lin, Ming Tang, Rongguang Ye, Shuai Wang, Guangxu Zhu, Yik-Chung Wu
Autonomous Driving Semantic Scene Hierarchical Federated Learning Layered Approach

September 27, 2024

September 24, 2024

Flight: A FaaS-Based Framework for Complex and Hierarchical Federated Learning
Nathaniel Hudson, Valerie Hayot-Sasson, Yadu Babuji, Matt Baughman, J. Gregory Pauloski, Ryan Chard, Ian Foster, Kyle Chard
New Framework Federated Learning Network Topology Complexity Level Hierarchical Federated Learning Flight Pattern Decentralized Machine

September 23, 2024

SHFL: Secure Hierarchical Federated Learning Framework for Edge Networks
Omid Tavallaie, Kanchana Thilakarathna, Suranga Seneviratne, Aruna Seneviratne, Albert Y. Zomaya
Edge Computing Edge Network Hierarchical Federated Learning Hierarchical Network

August 20, 2024

Security Assessment of Hierarchical Federated Deep Learning
D Alqattan, R Sun, H Liang, G Nicosia, V Snasel, R Ranjan, V Ojha
Adversarial Attack Adversarial Training Inference Time Hierarchical Federated Learning Training Time Attack Security Evaluation

August 17, 2024

Twin Sorting Dynamic Programming Assisted User Association and Wireless Bandwidth Allocation for Hierarchical Federated Learning
Rung-Hung Gau, Ting-Yu Wang, Chun-Hung Liu
Resource Allocation Convex Optimization Combinatorial Optimization Problem Hierarchical Federated Learning Bandwidth Allocation

August 9, 2024

Privacy-Preserved Taxi Demand Prediction System Utilizing Distributed Data
Ren Ozeki, Haruki Yonekura, Hamada Rizk, Hirozumi Yamaguchi
Contrastive Learning Raw Data Demand Prediction Hierarchical Federated Learning

July 25, 2024

HF-Fed: Hierarchical based customized Federated Learning Framework for X-Ray Imaging
Tajamul Ashraf, Tisha Madame
Federated Learning Part Whole Hierarchy Hierarchical Federated Learning X Ray Imaging

July 5, 2024

UAV-assisted Unbiased Hierarchical Federated Learning: Performance and Convergence Analysis
Ruslan Zhagypar, Nour Kouzayha, Hesham ElSawy, Hayssam Dahrouj, Tareq Y. Al-Naffouri
System Performance Convergence Analysis Hierarchical Federated Learning Stochastic Geometry UAV Assisted

July 1, 2024

FedRC: A Rapid-Converged Hierarchical Federated Learning Framework in Street Scene Semantic Understanding
Wei-Bin Kou, Qingfeng Lin, Ming Tang, Shuai Wang, Guangxu Zhu, Yik-Chung Wu
Semantic Scene Hierarchical Federated Learning Layered Approach

June 21, 2024

Towards Dynamic Resource Allocation and Client Scheduling in Hierarchical Federated Learning: A Two-Phase Deep Reinforcement Learning Approach
Xiaojing Chen, Zhenyuan Li, Wei Ni, Xin Wang, Shunqing Zhang, Yanzan Sun, Shugong Xu, Qingqi Pei
Reinforcement Learning Resource Allocation Task Scheduling Deep Deterministic Policy Gradient Hierarchical Federated Learning Energy Harvesting

May 27, 2024

Efficient Model Compression for Hierarchical Federated Learning
Xi Zhu, Songcan Yu, Junbo Wang, Qinglin Yang
Model Compression Collaborative Learning Hierarchical Federated Learning

May 25, 2024

Secure Hierarchical Federated Learning in Vehicular Networks Using Dynamic Client Selection and Anomaly Detection
M. Saeid HaghighiFard, Sinem Coleri
Anomaly Detection Client Selection Vehicular Network Hierarchical Federated Learning Robust Anomaly Detection

March 5, 2024

Leveraging Federated Learning and Edge Computing for Recommendation Systems within Cloud Computing Networks
Yaqian Qi, Yuan Feng, Xiangxiang Wang, Hanzhe Li, Jingxiao Tian
Edge Computing Recommendation System Edge Cloud Edge Intelligence Hierarchical Federated Learning Edge Deployment

March 3, 2024

Quantized Hierarchical Federated Learning: A Robust Approach to Statistical Heterogeneity
Seyed Mohammad Azimi-Abarghouyi, Viktoria Fodor
Heterogeneous Data Model Aggregation Robust Framework Hierarchical Federated Learning Statistical Heterogeneity Aggregated Gradient

February 4, 2024

Device Scheduling and Assignment in Hierarchical Federated Learning for Internet of Things
Tinghao Zhang, Kwok-Yan Lam, Jun Zhao
Internet of Thing Internet of Thing Device Good Thing Hierarchical Federated Learning Edge Server Task Assignment Device Scheduling

January 21, 2024

Differentially-Private Multi-Tier Federated Learning
Evan Chen, Frank Po-Chen Lin, Dong-Jun Han, Christopher G. Brinton
Differential Privacy Hierarchical Federated Learning Hierarchical Network

January 18, 2024

Hierarchical Federated Learning

Papers

Fast-Convergent and Communication-Alleviated Heterogeneous Hierarchical Federated Learning in Autonomous Driving

Hierarchical Federated ADMM

Hierarchical Federated Learning with Multi-Timescale Gradient Correction

Flight: A FaaS-Based Framework for Complex and Hierarchical Federated Learning

SHFL: Secure Hierarchical Federated Learning Framework for Edge Networks

Security Assessment of Hierarchical Federated Deep Learning

Twin Sorting Dynamic Programming Assisted User Association and Wireless Bandwidth Allocation for Hierarchical Federated Learning

Privacy-Preserved Taxi Demand Prediction System Utilizing Distributed Data

HF-Fed: Hierarchical based customized Federated Learning Framework for X-Ray Imaging

UAV-assisted Unbiased Hierarchical Federated Learning: Performance and Convergence Analysis

FedRC: A Rapid-Converged Hierarchical Federated Learning Framework in Street Scene Semantic Understanding

Towards Dynamic Resource Allocation and Client Scheduling in Hierarchical Federated Learning: A Two-Phase Deep Reinforcement Learning Approach

Efficient Model Compression for Hierarchical Federated Learning

Secure Hierarchical Federated Learning in Vehicular Networks Using Dynamic Client Selection and Anomaly Detection

Leveraging Federated Learning and Edge Computing for Recommendation Systems within Cloud Computing Networks

Quantized Hierarchical Federated Learning: A Robust Approach to Statistical Heterogeneity

Device Scheduling and Assignment in Hierarchical Federated Learning for Internet of Things

Differentially-Private Multi-Tier Federated Learning

Hierarchical Federated Learning in Multi-hop Cluster-Based VANETs

Mobility Accelerates Learning: Convergence Analysis on Hierarchical Federated Learning in Vehicular Networks