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A novel hot data identification mechanism for NAND flash memory

机译:NAND闪存的新型热数据识别机制

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摘要

Hot data identification plays a very important role in NAND flash memory because it can improve the efficiency of garbage collection and decrease the degree of wear leveling. Existing hot data identification mechanisms have drawbacks in terms of their memory-space overhead and the true identification of hot data. To address these problems, this paper proposes a novel hot data identification mechanism. This mechanism mainly consists of kernel density estimation and a hot degree function. The kernel density estimation is used to build the kernel density function of the read and write operations by monitoring them in the NAND flash memory. That is, the kernel density function can be used for preliminary estimation of the probability distribution of the hot and cold data in NAND flash memory. After preliminary estimation of the kernel density function, the hot degree function is introduced to accurately identify the hot data in the NAND flash memory. Experimental results show that the proposed mechanism performs better than existing hot data identification mechanisms in terms of the false identification ratio between hot data and memory-space overheads.
机译:热数据识别在NAND闪存中起着非常重要的作用,因为它可以提高垃圾收集的效率并降低损耗均衡的程度。现有的热数据识别机制就其存储空间开销和对热数据的真实识别而言具有缺点。为了解决这些问题,本文提出了一种新颖的热数据识别机制。该机制主要包括核密度估计和热度函数。内核密度估计用于通过监视NAND闪存中的读写操作来构建内核密度函数。即,内核密度函数可用于对NAND闪存中的热数据和冷数据的概率分布进行初步估计。在初步估计内核密度函数之后,引入了热度函数以准确识别NAND闪存中的热数据。实验结果表明,在热数据和内存空间开销之间的错误识别率方面,该机制的性能优于现有的热数据识别机制。

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