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PROBABILISTIC PAGE REPLACEMENT POLICY IN BUFFER CACHE MANAGEMENT FOR FLASH-BASED CLOUD DATABASES

机译:基于Flash的云数据库缓冲区缓存管理中的概率页替换策略

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摘要

In the fast evolution of storage systems, the newly emerged flash memory-based Solid State Drives (SSDs) are becoming an important part of the computer storage hierarchy. Amongst the several advantages of flash-based SSDs, high read performance, and low power consumption are of primary importance. Amongst its few disadvantages, its asymmetric I/O latencies for read, write and erase operations are the most crucial for overall performance. In this paper, we proposed two novel probabilistic adaptive algorithms that compute the future probability of reference based on recency, frequency, and periodicity of past page references. The page replacement is performed by considering the probability of reference of cached pages as well as asymmetric read-write-erase properties of flash devices. The experimental results show that our proposed method is successful in minimizing the performance overheads of flash-based systems as well as in maintaining the good hit ratio. The results also justify the utility of a genetic algorithm in maximizing the overall performance gains.
机译:在存储系统的快速演变中,基于新出现的闪存的固态驱动器(SSD)正在成为计算机存储层次结构的重要组成部分。在基于闪存的SSD,高读取性能和低功耗中的几个优点中,重要的重要性。在其几个缺点中,其用于读取,写和擦除操作的不对称I / O潜伏是整体性能最为关键的。在本文中,我们提出了两种新的概率自适应算法,该算法基于过去页面引用的新近度,频率和周期性来计算引用的未来概率。通过考虑缓存页面的参考概率以及闪存器件的不对称读写擦除属性来执行页面替换。实验结果表明,我们的提出方法在最大限度地减少了基于闪存的系统的性能开销以及保持良好的命中率方面是成功的。结果还证明了遗传算法在最大化整体性能收益方面的效用。

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