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A hybrid disaster-tolerant model with DDF technology for MooseFS open-source distributed file system

机译:MooseFS开源分布式文件系统的具有DDF技术的混合容灾模型

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In a distributed file system (DFS), a disaster-tolerant model provides high data security in the data disaster event by geographically isolates the backup data, while the hot-backup model provides high availability when the main server is offline. Therefore, the combined model is widely concerned in multiple fields. However, previous investigations have neglected to the disaster tolerance for open-source distributed file systems. When a server run into a fault status and performs backup switch, the remote data center cannot receive any data replicas. We proposed a hybrid model in this work to provide disaster-tolerance especially for open-source DFS by build geographically isolate replicas. In addition, we optimize the model with direct data fetch (DDF) technology. DDF can bypass the main server, and retrieve data directly from the data node. The model was implemented on an open-source DFS named MooseFS. Compared with HDFS and IBM/PPRC, the hybrid model with DDF provides a strong performance boost to the hybrid model during the switch procedure, and this hybrid model performs best for storage of large amount of files in small size.
机译:在分布式文件系统(DFS)中,容灾模型通过在地理上隔离备份数据来提供数据灾难事件中的高数据安全性,而热备份模型在主服务器脱机时提供了高可用性。因此,组合模型在多个领域受到广泛关注。但是,以前的调查都忽略了开源分布式文件系统的容灾能力。当服务器进入故障状态并执行备份切换时,远程数据中心将无法接收任何数据副本。我们在这项工作中提出了一种混合模型,旨在通过构建地理上隔离的副本来提供容灾能力,特别是针对开源DFS。此外,我们使用直接数据提取(DDF)技术优化了模型。 DDF可以绕开主服务器,并直接从数据节点检索数据。该模型是在名为MooseFS的开源DFS上实现的。与HDFS和IBM / PPRC相比,具有DDF的混合模型在切换过程中为混合模型提供了强大的性能提升,并且该混合模型对于存储大量小尺寸文件的性能最佳。

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