PDS: An I/O-Efficient Scaling Scheme for Parity Declustered Data Layout

Abstract

Parity declustering is widely deployed in erasure coded storage systems so as to provide fast recovery and high data availability. However, to perform scaling on such RAIDs, it is necessary to preserve the parity declustered data layout so as to guarantee the RAID performance after scaling. Unfortunately, existing scaling algorithms fail to achieve this goal so they can not be applied for scaling RAIDs which have deployed parity declustering. To address this challenge, we develop an efficient scaling algorithm called PDS (Parity Declustering Scaling). In particular, we first employ an auxiliary Balanced Incomplete Block Design (BIBD) to define the data migrations during scaling so as to preserve parity declustered data layout, and then define the addressing algorithm in the scaled system based on the migrations. We provide theoretical proofs to show that PDS preserves the parity declustered data layout, which is the basis for scaling RAIDs with parity declustering, and also theoretically prove that PDS achieves the even distribution of data/parity blocks after scaling and requires only the minimal data migrations. To show the performance of PDS, we implement it in MD in Linux Kernel, and conduct experiments with real-world traces. Results show PDS can reduce 89.70% of data migration time and 24.44% of user response time during scaling on average, compared with the round-robin scheme.