基于自动回归的小文件在线备份方案

Peng-di YE , Wen-bin YAO , Xiao-yong LI
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引用次数: 0

摘要

在低系统开销的情况下减少备份窗口是海量小文件环境下备份系统面临的挑战。本文提出了一种新的基于自回归的小文件在线备份方案(ABBSF),通过提高带宽资源在正常情况下的利用率来实现这一目标。ABBSF利用单传输模式和包传输模式来处理小文件。ABBSF采用单次传输的方式,周期性地向备份端发送一个小文件,并在此过程中采集网络情况。根据这些网络性能信息,建立基于自回归的模型,预测下一时间段的可用网络带宽。同时,提供预测步长控制,使预测模型得到更好的利用,保持较低的系统开销。ABBSF在预测的基础上,为包的传输制定合适的传输策略。最后,采用包传输将多个文件打包并发送到备份端。实验表明,ABBSF在备份小文件时具有较好的预测性能,系统开销较低,可以充分利用网络带宽。
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Autoregressive-based online backup scheme for small files

Reduce backup window with lower system overheads is a challenge for backup system in massive small files environment. In this article, a new autoregressive-based online backup scheme for small files (ABBSF) is presented to achieve the goal by enhancing the utilization ratio of bandwidth resource in normal times. ABBSF exploits single transfer pattern and package transfer pattern to deal with small files. ABBSF employs single transfer to send one small file to the backup side periodically, and collects the network situation in this procedure. According to these network performance information, it builds autoregressive-based model for predicting available network bandwidth in the next period. Meanwhile, it provides predictive step length control to make more utilization of predictive model for maintaining low system overheads. On the basis of prediction, ABBSF makes appropriate transfer policy for package transfer. Finally, it employs package transfer to pack several files and sent them to the backup side. Experiments show that ABBSF has a good performance of prediction with relatively low system overheads to make full use of network bandwidth when backup small files.

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