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Paper · arXiv

Hidden in Rounds: Predicting the Time Cost of 802.11 Contention in Federated Learning

Federated learning over IEEE~802.11 shares the wireless channel among clients that send model updates. We use ns-3 to measure the frame-delivery ratio and saturation throughput for different client densities and offered loads. A separate FedAvg trainer uses the frame-delivery ratio as a first-order proxy for the update-admission probability and uses an equation to estimate communication time. The method does not simulate the delivery of a complete model update or measure end-to-end training time. Across 720 evaluated runs with two datasets, two data partitions, six client densities, six offered loads, and five seeds, all runs reached their predefined target accuracy within the round budge...

AuthorsSatwat Bashir, Tasos Dagiuklas
Primary categorycs.LG
Published11 September 2026
Last updated at source11 September 2026
cs.LGcs.DC
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