Dayu: Fast and Low-interference Data Recovery in Very-large Storage Systems

This paper investigates I/O and failure traces from a realworld large-scale storage system: it finds that because of the scale of the system and because of the imbalanced and dynamic foreground traffic, no existing recovery protocol can compute a high-quality re-replicating strategy in a short time. To address this problem, this paper proposes Dayu, a timeslot based recovery architecture. For each timeslot, Dayu only schedules a subset of tasks which are expected to be finished in this timeslot: this approach reduces the computation overhead and naturally can cope with the dynamic foreground traffic. In each timeslot, Dayu incorporates a greedy algorithm with convex hull optimization to achieve both high speed and high quality. Our evaluation in a 1,000-node cluster and in a 3,500-node simulation both confirm that Dayu can outperform existing recovery protocols, achieving high speed and high quality.