摘要
在大型存储系统中,改善离散小数据块读操作的性能已成为提高整个存储系统I/O性能的关键因素。针对这种情况,本文设计并实现了一种系统CBSS(correlative blocks speedup system)。该系统采用一种启发式算法,综合考虑数据访问时间的局部性和全局性,在文件系统和存储设备之间挖掘数据块的相关性,并根据取得的结果进行预取和数据块布局的物理调整,使整个存储系统性能能够平滑地不间断改善。实验结果显示,CBSS能有效改进系统的I/O性能,且不需要改变文件系统和存储设备的数据结构,具有广泛的适应性。
In the large storage system, the operation of continuously reading discrete small blocks severely impacts the I/O performance. To solve this problem, this paper designs and implements a system, CBSS(correlative blocks speedup system), which implements precise prefeteh and regulates the data distribution according the small blocks correlations, mined by a novel heuristic algorithm between the file system and block device. The system performance can be improved evenly and continuously without interruption and sudden state transitions. Furthermore, compared with other axgorithms,this heuristic algorithm thinks about both the locality and the globality of the correlations. Through the experiments,it has been proved that CBSS and the algorithm are effective and the system I/O performance can be enhanced distinctly. Furthermore, the prototype can be used universally without modifying the file system and the storage devices.
出处
《计算机科学》
CSCD
北大核心
2006年第6期69-72,共4页
Computer Science
基金
国家自然科学基金项目资助
编号:60273073。
关键词
相关性
块设备
启发式
Correlations, Block device, Heuristic