mlsanityData to 7 Oct 2026

PeerFL: A Simulator for Peer-to-Peer Federated Learning at Scale

arXiv 2405.17839 ↗First posted 28 May 2024cs.DC cs.AIcited by 1

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Abstract (arXiv)

This work integrates peer-to-peer federated learning tools with NS3, a widely used network simulator, to create a novel simulator designed to allow heterogeneous device experiments in federated learning. This cross-platform adaptability addresses a critical gap in existing simulation tools, enhancing the overall utility and user experience. NS3 is leveraged to simulate WiFi dynamics to facilitate federated learning experiments with participants that move around physically during training, leading to dynamic network characteristics. Our experiments showcase the simulator's efficiency in computational resource utilization at scale, with a maximum of 450 heterogeneous devices modelled as participants in federated learning. This positions it as a valuable tool for simulation-based investigations in peer-to-peer federated learning. The framework is open source and available for use and extension to the community.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 10 of its 21 references that are in the map. First posted on arXiv 28 May 2024.

Builds on

10 of 21 references.

References · 10

  1. 2016Communication-Efficient Learning of Deep Networks from Decentralized Datacited by 7,592
  2. 2014Explaining and Harnessing Adversarial Examplescited by 7,287
  3. 2017Towards Deep Learning Models Resistant to Adversarial Attackscited by 6,326
  4. 2017Ensemble Adversarial Training: Attacks and Defensescited by 833
  5. 2021Federated Learning for Internet of Things: A Comprehensive Surveycited by 247
  6. 2019BrainTorrent: A Peer-to-Peer Environment for Decentralized Federated Learningcited by 115
  7. 2021Federated Learning on the Road: Autonomous Controller Design for Connected and Autonomous Vehiclescited by 26
  8. 2022Towards Effective Clustered Federated Learning: A Peer-to-peer Framework with Adaptive Neighbor Matchingcited by 24
  9. 2021On-device Federated Learning with Flowercited by 13
  10. 2021Byzantine Fault-Tolerance in Peer-to-Peer Distributed Gradient-Descentcited by 6

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