A Rack-Aware Pipeline Repair Scheme for Erasure-Coded Distributed Storage Systems
Tong Liu, Shakeel Alibhai, Xubin He · 2020
Nowadays, modern industry data centers have employed erasure codes to provide reliability for large amounts of data at a low cost. Although erasure codes provide optimal storage efficiency, they suffer from high repair costs compared to traditional three-way replication: when a data miss occurs in a data center, erasure codes would require high disk usage and network bandwidth consumption across nodes and racks to repair the failed data. In this paper, we propose RPR, a rack-aware pipeline repair scheme for erasure-coded distributed storage systems. RPR for the first time investigates the insights of the racks, and explores the connection between the node level and rack level to help improve the repair performance when a single failure or multiple failures occur in a data center. The evaluation results on several common RS code configurations show that, for single-block failures, our RPR scheme reduces the total repair time by up to 81.5% compared to the traditional RS code repair method and 50.2% compared to the state-of-the-art CAR algorithm. For multi-block failures, RPR reduces the total repair time and cross-rack data transfer traffic by up to 64.5% and 50%, respectively, over the traditional repair.