mlsanityData to 14 Oct 2026

Decentralized Federated Learning: A Survey and Perspective

arXiv 2306.01603 ↗First posted 2 Jun 2023cs.LG cs.CY cs.DCcited by 86

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Abstract (arXiv)

Federated learning (FL) has been gaining attention for its ability to share knowledge while maintaining user data, protecting privacy, increasing learning efficiency, and reducing communication overhead. Decentralized FL (DFL) is a decentralized network architecture that eliminates the need for a central server in contrast to centralized FL (CFL). DFL enables direct communication between clients, resulting in significant savings in communication resources. In this paper, a comprehensive survey and profound perspective are provided for DFL. First, a review of the methodology, challenges, and variants of CFL is conducted, laying the background of DFL. Then, a systematic and detailed perspective on DFL is introduced, including iteration order, communication protocols, network topologies, paradigm proposals, and temporal variability. Next, based on the definition of DFL, several extended variants and categorizations are proposed with state-of-the-art (SOTA) technologies. Lastly, in addition to summarizing the current challenges in the DFL, some possible solutions and future research directions are also discussed.

Key facts. Cited by 86 papers in the map (data through 14 Oct 2026). Builds on 116 of its 248 references that are in the map. First posted on arXiv 2 Jun 2023.

Builds on

116 of 248 references.

References · 116

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  2. 2016Communication-Efficient Learning of Deep Networks from Decentralized Datacited by 7,669
  3. 2019EfficientNet: Rethinking Model Scaling for Convolutional Neural Networkscited by 6,442
  4. 2018MobileNetV2: Inverted Residuals and Linear Bottleneckscited by 4,795
  5. 2019Advances and Open Problems in Federated Learningcited by 3,046
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  10. 2018How To Backdoor Federated Learningcited by 765
  11. 2020The Future of Digital Health with Federated Learningcited by 633
  12. 2018Federated Learning for Mobile Keyboard Predictioncited by 572
38 more
  1. 2019Federated Learning with Differential Privacy: Algorithms and Performance Analysiscited by 536
  2. 2020An Efficient Framework for Clustered Federated Learningcited by 511
  3. 2019Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraintscited by 503
  4. 2017Can Decentralized Algorithms Outperform Centralized Algorithms? A Case Study for Decentralized Parallel Stochastic Gradient Descentcited by 502
  5. 2021Towards Personalized Federated Learningcited by 464
  6. 2019Robust and Communication-Efficient Federated Learning from Non-IID Datacited by 419
  7. 2018Adaptive Federated Learning in Resource Constrained Edge Computing Systemscited by 409
  8. 2019Federated Learning in Mobile Edge Networks: A Comprehensive Surveycited by 408
  9. 2019Fair Resource Allocation in Federated Learningcited by 394
  10. 2019A Survey on Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protectioncited by 374
  11. 2020SplitFed: When Federated Learning Meets Split Learningcited by 310
  12. 2020Data Poisoning Attacks Against Federated Learning Systemscited by 275
  13. 2021Federated Learning for Internet of Things: A Comprehensive Surveycited by 252
  14. 2019Decentralized Stochastic Optimization and Gossip Algorithms with Compressed Communicationcited by 221
  15. 2021Federated Learning for Smart Healthcare: A Surveycited by 184
  16. 2019FedHealth: A Federated Transfer Learning Framework for Wearable Healthcarecited by 182
  17. 2020Threats to Federated Learning: A Surveycited by 178
  18. 2020Federated Continual Learning with Weighted Inter-client Transfercited by 161
  19. 2017Asynchronous Decentralized Parallel Stochastic Gradient Descentcited by 159
  20. 2018Stochastic Gradient Push for Distributed Deep Learningcited by 152
  21. 2018Multi-Institutional Deep Learning Modeling Without Sharing Patient Data: A Feasibility Study on Brain Tumor Segmentationcited by 149
  22. 2020Federated Learning for Internet of Things: Recent Advances, Taxonomy, and Open Challengescited by 139
  23. 2022Decentralized Federated Learning: Fundamentals, State of the Art, Frameworks, Trends, and Challengescited by 138
  24. 2021FedScale: Benchmarking Model and System Performance of Federated Learning at Scalecited by 136
  25. 2017Network Topology and Communication-Computation Tradeoffs in Decentralized Optimizationcited by 122
  26. 2019BrainTorrent: A Peer-to-Peer Environment for Decentralized Federated Learningcited by 117
  27. 2021Multi-Center Federated Learning: Clients Clustering for Better Personalizationcited by 113
  28. 2019Decentralized Deep Learning with Arbitrary Communication Compressioncited by 111
  29. 2018Blockchained On-Device Federated Learningcited by 106
  30. 2019Reliable Federated Learning for Mobile Networkscited by 92
  31. 2019Robust Federated Learning in a Heterogeneous Environmentcited by 90
  32. 2019Peer-to-peer Federated Learning on Graphscited by 85
  33. 2022Federated Learning Enables Big Data for Rare Cancer Boundary Detectioncited by 84
  34. 2019Federated Learning with Cooperating Devices: A Consensus Approach for Massive IoT Networkscited by 79
  35. 2021Federated Learning Meets Blockchain in Edge Computing: Opportunities and Challengescited by 76
  36. 2019Federated Learning for Edge Networks: Resource Optimization and Incentive Mechanismcited by 75
  37. 2019Decentralized Federated Learning: A Segmented Gossip Approachcited by 64
  38. 2022Communication-Efficient Stochastic Zeroth-Order Optimization for Federated Learningcited by 59

50 most cited of 116 All 116 (JSON)

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 10; 2024: 21; 2025: 31; 2026: 24.

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  1. 2023Federated Learning for Connected and Automated Vehicles: A Survey of Existing Approaches and Challengescited by 40
  2. 2023A Survey on Decentralized Federated Learningcited by 27
  3. 2024Overcoming Data and Model Heterogeneities in Decentralized Federated Learning via Synthetic Anchorscited by 21
  4. 2025Decentralized Low-Rank Fine-Tuning of Large Language Modelscited by 14
  5. 2024Communication-Efficient Multimodal Federated Learning: Joint Modality and Client Selectioncited by 11
  6. 2024One-Shot Sequential Federated Learning for Non-IID Data by Enhancing Local Model Diversitycited by 8
  7. 2024Byzantine-Robust Aggregation for Securing Decentralized Federated Learningcited by 7
  8. 2025A Privacy-Preserving Federated Framework with Hybrid Quantum-Enhanced Learning for Financial Fraud Detectioncited by 7
  9. 2023DFedADMM: Dual Constraints Controlled Model Inconsistency for Decentralized Federated Learningcited by 6
  10. 2024SoK: Blockchain-Based Decentralized AI (DeAI)cited by 6
  11. 2023Asymmetrically Decentralized Federated Learningcited by 5
  12. 2023FedMFS: Federated Multimodal Fusion Learning with Selective Modality Communicationcited by 4
38 more
  1. 2024DFML: Decentralized Federated Mutual Learningcited by 4
  2. 2024Decentralized Federated Learning with Model Caching on Mobile Agentscited by 4
  3. 2024NTK-DFL: Enhancing Decentralized Federated Learning in Heterogeneous Settings via Neural Tangent Kernelcited by 4
  4. 2024Decentralized Personalized Federated Learning based on a Conditional Sparse-to-Sparser Schemecited by 3
  5. 2024Decentralized Federated Learning with Gradient Tracking over Time-Varying Directed Networkscited by 3
  6. 2025AutoDFL: A Scalable and Automated Reputation-Aware Decentralized Federated Learningcited by 3
  7. 2025Research in Collaborative Learning Does Not Serve Cross-Silo Federated Learning in Practicecited by 3
  8. 2023Sparse Decentralized Federated Learningcited by 2
  9. 2023Digital Ethics in Federated Learningcited by 2
  10. 2023Robust Collaborative Inference with Vertically Split Data Over Dynamic Device Environmentscited by 2
  11. 2024Initialisation and Network Effects in Decentralised Federated Learningcited by 2
  12. 2024Boosting the Performance of Decentralized Federated Learning via Catalyst Accelerationcited by 2
  13. 2024Using Diffusion Models as Generative Replay in Continual Federated Learning -- What will Happen?cited by 2
  14. 2025Decentralised Resource Sharing in TinyML: Wireless Bilayer Gossip Parallel SGD for Collaborative Learningcited by 2
  15. 2025Robust Knowledge Distillation in Federated Learning: Counteracting Backdoor Attackscited by 2
  16. 2025DICE: Data Influence Cascade in Decentralized Learningcited by 2
  17. 2025Towards Adapting Federated & Quantum Machine Learning for Network Intrusion Detection: A Surveycited by 2
  18. 2025Unified Privacy Guarantees for Decentralized Learning via Matrix Factorizationcited by 2
  19. 2026Certified Unlearning in Decentralized Federated Learningcited by 2
  20. 2026Diffusion-Guided Semantic Consistency for Multimodal Heterogeneitycited by 2
  21. 2023Energy-Efficient and Real-Time Sensing for Federated Continual Learning via Sample-Driven Controlcited by 1
  22. 2023Federated Learning over Hierarchical Wireless Networks: Training Latency Minimization via Submodel Partitioningcited by 1
  23. 2024Federated learning in food researchcited by 1
  24. 2024OledFL: Unleashing the Potential of Decentralized Federated Learning via Opposite Lookahead Enhancementcited by 1
  25. 2024FedPAE: Peer-Adaptive Ensemble Learning for Asynchronous and Model-Heterogeneous Federated Learningcited by 1
  26. 2024Exposing the Vulnerability of Decentralized Learning to Membership Inference Attacks Through the Lens of Graph Mixingcited by 1
  27. 2025Performance Analysis of Decentralized Federated Learning Deploymentscited by 1
  28. 2025Decentralized Federated Dataset Dictionary Learning for Multi-Source Domain Adaptationcited by 1
  29. 2025FedSKD: Aggregation-free Model-heterogeneous Federated Learning via Multi-dimensional Similarity Knowledge Distillation for Medical Image Classificationcited by 1
  30. 2025Sharp Gaussian approximations for Decentralized Federated Learningcited by 1
  31. 2025FedSEA-LLaMA: A Secure, Efficient and Adaptive Federated Splitting Framework for Large Language Modelscited by 1
  32. 2025On the Fast Adaptation of Delayed Clients in Decentralized Federated Learning: A Centroid-Aligned Distillation Approachcited by 1
  33. 2025Efficient Asynchronous Federated Evaluation with Strategy Similarity Awareness for Intent-Based Networking in Industrial Internet of Thingscited by 1
  34. 2026Decentralized Time-Varying Optimization for Streaming Data via Temporal Weightingcited by 1
  35. 2026Centralized vs Decentralized Federated Learning: A trade-off performance analysiscited by 1
  36. 2026Automated Byzantine-Resilient Clustered Decentralized Federated Learning for Battery Intelligence in Connected EVscited by 1
  37. 2024MSfusion: A Dynamic Model Splitting Approach for Resource-Constrained Machines to Collaboratively Train Larger Modelscited by 0
  38. 2024Impact of Network Topology on Byzantine Resilience in Decentralized Federated Learningcited by 0

50 most cited of 86 All 86 (JSON)