Baymac Official

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We simulated a 50-node edge network with varying channel SNR and data arrival rates (Poisson-distributed, λ = 5–20 packets/sec). Each node ran either a local classifier (CNN) or offloaded to a cloud server. Baymac’s Bayesian model updated every 100 ms using observed latency and accuracy feedback. Performance metrics: baymac

Baymac extends these by jointly optimizing what to compute locally and when to transmit using a Bayesian reward model. : There are also mentions of materials and

Existing solutions include:

Baymac reduced latency by 18% compared to the best baseline (threshold-based) and improved energy efficiency by 28%. Baymac’s Bayesian model updated every 100 ms using