Mitigating False Collisions in Partition-Based Concurrency Control

Abstract

Modern storage systems must scale request processing across many cores, making efficient concurrency control essential. Data partitioning routes operations to execution contexts that own portions of system state, reducing synchronization overhead but potentially introducing false collisions: unnecessary serialization imposed by partition boundaries rather than true data dependencies. False collisions arise when operations span partitions (e.g., large or misaligned I/Os) or when static provisioning mismatches demand, reducing parallelism and increasing queueing delay. We present two complementary mechanisms to mitigate false collisions in partitioned execution frameworks. Relaxed Data Partitioning (RDP) executes common partition-spanning I/Os in fine-grained partitions while synchronizing only the additional accessed regions via targeted, partition-aware locking. Elastic Data Partitioning (EDP) dynamically adjusts the number of active execution partitions through auxiliary execution contexts, increasing parallelism without changing ownership or requiring online repartitioning. We instantiate RDP and EDP in WAFL's hierarchical partitioning framework and evaluate them on multiple platforms and representative request streams. RDP improves throughput by up to 105%, EDP by up to 82%, and together by up to 145%, while imposing negligible overhead.