A Stripe-Schedule Aware Repair Technique in the Heterogeneous Network for Erasure-coded Clusters

More and more commodity storage systems use erasure code to tolerate faults. When reconsidering the recovery problem in a multi-stripe level and heterogeneous network for the erasure-coded cluster, efficiently generating an optimal multi-stripe recovery solution that reduces recovery time remains a challenging and time-consuming task. Previous works either use a greedy algorithm that may fall into the local-optimal and has low performance or use a meta-heuristic algorithm with a long search time and low efficiency.In this paper, we propose a Stripe-schedule Aware Repair (SARepair) technique for multi-stripe recovery in heterogeneous erasure-coded clusters. By carefully examining the metadata of blocks, SARepair intelligently adjusts the recovery solution for each stripe and obtains another multi-stripe solution with less recovery time in a computationally efficient manner. It then tolerates worse solutions to overcome the local-optimal and uses a rollback mechanism to adjust search regions to further reduce recovery time. Moreover, instead of reading blocks sequentially from each node, SARepair also selectively schedules the reading order for each block to reduce the memory overhead. We prototype SARepair and show via both simulations and Amazon EC2 experiments that the recovery time can be reduced by up to 68% over a state-of-the-art recovery approach while keeping time complexity and memory overhead low.