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We present AdaptRaft, a variant of the Raft consensus algorithm that dynamically adjusts its timing parameters using a lightweight online learning model, reducing tail latency by up to 34% in geo-distributed deployments.
Informal notes clarifying which safety and liveness properties Raft provides under which assumptions, written while preparing a talk on adaptive consensus.
A structured survey of Byzantine fault-tolerant consensus protocols deployed since 2015, identifying the practical trade-offs between safety, liveness, and throughput that are often obscured in theoretical treatments.