分级存储系统中一种数据自动迁移方法

An Approach for Migrating Data Adaptively in Hierarchical Storage Systems

分级存储系统通过将数据在不同性能设备间动态迁移以达到高性能.已有分级存储系统未能充分利用负载信息导致数据迁移严重影响应用性能.提出了一种分级存储系统中的数据自动迁移方法AutoMig,目标是提高前台应用的I?O性能.AutoMig综合文件访问历史、文件大小、设备利用情况等参数,对文件进行动态分级,并使用LRU队列维护快速存储设备中的文件状态;挖掘关联文件用于自动预取;针对不同文件迁移操作采取不同的速率控制策略.对降级操作,根据负载变化动态调整迁移速率,对回迁操作则采取尽力而为的策略.在分级存储系统中的应用表明,与已有方法相比,AutoMig有效缩短了前台I?O响应时间.

Hierarchical storage management （HSM） constructs a storage system with different types of devices, e. g. , SCSI disks, SATA disks, FC disks and even SSD disks. The goal is to obtain large capacity with low cost. In order to achieve high performance, hierarchical storage management systems classify data dynamically and move them between fast devices and slow devices efficiently. However, almost all existing HSM systems have some limitations. Especially, without taking full advantage of the information from workloads, they make data migration affect application performance noticeably. AutoMig, an approach to automatically migrate data in a HSM system is proposed to enhance I/O performance of foreground applications. Firstly, AutoMig dynamically classifies files according to file access history, file size and storage utilization. Furthermore, an LRU queue is used to maintain the files in the fast devices. Secondly, it finds correlated files for automatic prefetching with data mining technology. Thirdly, AutoMig applies different policies to files migrating actions. It adaptively adjusts the migration rate according to varying workloads for migrating out actions while uses the as-fast-as-possible policy for migrating back actions. The application in a hierarchical storage system showes that AutoMig can effectively shorten foreground I/O response time compared with existing approaches.