Adaptive Snapshot Scheduling for Asynchronous Replication Under Bursty Write Workloads: A Simulation Study of Recovery-Point Compliance
Abstract
Fixed snapshot intervals used for asynchronous replication can either waste resources during quiet periods or violate recovery-point objectives during bursts of write activity. We evaluated an adaptive scheduling policy that adjusted snapshot frequency according to recent changed-data rate, replication backlog, and available bandwidth. A discrete-event simulation replayed 90 production-like workload traces covering databases, virtual machines, and file services under four network-capacity profiles. Recovery-point compliance, snapshot count, replication traffic, and backlog duration were compared with 5-, 15-, and 30-minute fixed schedules. The adaptive policy maintained the target recovery point in 96.8% of evaluated intervals, compared with 88.1% for the best fixed schedule under bursty conditions. It reduced snapshot operations by 24% relative to the 5-minute policy and lowered prolonged backlog episodes by 37%. Performance deteriorated when bandwidth estimates lagged sudden network degradation, but incorporating a conservative backlog margin mitigated this effect. Adaptive snapshot scheduling can improve recovery-point compliance without permanently operating at the most aggressive interval. Practical implementations should combine workload-aware timing with explicit safeguards for estimation error and network volatility.
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