School of Computer and Electronic Information, Guangxi University, Nanning 530004, China.
Guangxi Intelligent Digital Services Research Center of Engineering Technology, Nanning 530004, China.
Sensors (Basel). 2023 Jun 22;23(13):5809. doi: 10.3390/s23135809.
Erasure-code-based storage systems suffer from problems such as long repair time and low I/O performance, resulting in high repair costs. For many years, researchers have focused on reducing the cost of repairing erasure-code-based storage systems. In this study, we discuss the demerits of node selecting, data transferring and data repair in erasure-code-based storage systems. Based on the network topology and node structure, we propose SDNC-Repair, a cooperative data repair strategy based on erasure code for SDS (Software Defined Storage), and describe its framework. Then, we propose a data source selection algorithm that senses the available network bandwidth between nodes and a data flow scheduling algorithm in SDNC-Repair. Additionally, we propose a data repair method based on node collaboration and data aggregation. Experiments illustrate that the proposed method has better repair performance under different data granularities. Compared to the conventional repair method, although the SDNC-Repair is more constrained by the cross-rack bandwidth, it improves system throughput effectively and significantly reduces data repair time in scenarios where multiple nodes fail and bandwidth is limited.
基于纠删码的存储系统存在修复时间长、I/O 性能低等问题，导致修复成本高。多年来，研究人员一直致力于降低基于纠删码的存储系统的修复成本。在这项研究中，我们讨论了基于纠删码的存储系统中节点选择、数据传输和数据修复的缺点。基于网络拓扑和节点结构，我们提出了 SDNC-Repair，这是一种基于纠删码的 SDS（软件定义存储）的协作数据修复策略，并描述了其框架。然后，我们提出了一种在 SDNC-Repair 中感知节点间可用网络带宽的数据源选择算法和一种数据流调度算法。此外，我们还提出了一种基于节点协作和数据聚合的数据修复方法。实验表明，在不同的数据粒度下，所提出的方法具有更好的修复性能。与传统的修复方法相比，虽然 SDNC-Repair 受到跨机架带宽的限制更大，但在多个节点故障且带宽有限的情况下，它可以有效地提高系统吞吐量，并显著减少数据修复时间。
