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Research on Data Recovery Technology Based on Flash Memory Device

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Algorithms and Architectures for Parallel Processing (ICA3PP 2018)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11335))

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Abstract

Due to the significant internal structural difference between flash memory devices and traditional mechanical hard disks, the data recovery technology for traditional mechanical hard disks cannot be directly applied to flash memory devices. Therefore, there is an urgent need to explore a data recovery method specific to flash storage devices. On the premise of obtaining the mirror data structure parameters of the flash memory chip, through analyzing the underlying data from the said chip, determination and analysis can be done to the interleave type of data on the physical structure. And according to the different interleaving granularity, universal formulas can be generalized one by one. Select the data of valid block to be put into the formula which is suitable for interleaving granularity, and then calculate the corresponding logical address. Finally, write the buffers one by one in the order indicated by the logical address to achieve the data recovery. Under the circumstance where the structure parameters cannot be obtained due to mechanical malfunction, to develop a recovery strategy based on an unknown algorithm by constructing a learning disk can be both practical and instructive.

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Acknowledgement

This paper is supported by the Beijing Municipal Natural Science Foundation (No. 4172053).

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Correspondence to Lele Guan , Jun Zheng or Chenyang Li .

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Guan, L., Zheng, J., Li, C., Wang, D. (2018). Research on Data Recovery Technology Based on Flash Memory Device. In: Vaidya, J., Li, J. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2018. Lecture Notes in Computer Science(), vol 11335. Springer, Cham. https://doi.org/10.1007/978-3-030-05054-2_20

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  • DOI: https://doi.org/10.1007/978-3-030-05054-2_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-05053-5

  • Online ISBN: 978-3-030-05054-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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