Abstract
Flash translation layers play an important role in determining the storage performance and lifetime of NAND flash-based electronics devices. And file system designs are undergoing rapid evolution to exploit the potentials of flash memory. Although many compression Flash Translation Layer (FTLs) have been designed, there is serious overhead for the software compression or even hardware compression and decompression process which are inevitable. In this paper, we present a partition FTL which can distinguish the file system metadata and user data. After the division of the mapping table, we add transparent data compression to the user data part, a logical partition compression, called pcFTL, which reduces the amount of data written into NAND flash memory. In addition, no more decrease in (Solid state drive) SSD performance due to no filesystem metadata compression overhead. Transplanting compression on user data part, other than file system data part not only benefit disk performance but also save SDRAM space. pcFTL is one kind of filesystem suited FTL design.
Our evaluations with three real-world workloads show that pcFTL successfully enhances storage performance and lifetime by minimizing the Write Amplification Factor (WAF) by up to 30–40% compared to the case without compression support, for those TXT files. Moreover, pcFTL can improve write performance by up to 10%.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Nagel, L., Süß, T., et al.: Time-efficient Garbage collection in SSDs (2018)
Wei, X., Yong, C.: An adaptive separation-aware FTL for improving the efficiency of garbage collection in SSDs. In: IEEE/ACM International Symposium on Cluster (2014)
Chang, L.P.: On efficient wear leveling for large-scale flash-memory storage systems. In: ACM Symposium on Applied Computing. ACM (2007)
Shi, X., Wu, F., Wang, S., Xie, C., Lu, Z.: Program error rate-based wear leveling for NAND flash memory. In: 2018 Design, Automation & Test in Europe Conference & Exhibition (DATE), Dresden (2018)
Kim, J.S.: zFTL: power-efficient data compression support for NAND flash-based consumer electronics devices. IEEE Trans. Consum. Electron. 57, 1148–1156 (2011)
Zhou, Y., Wu, F., Huang, P., et al.: Understanding and alleviating the impact of the flash address translation on solid state devices. J. ACM Trans. Storage 13, 14 (2017)
Wang, M., Zhang, Y., Kang, W.: ZFTL: a zone-based flash translation layer with a two-tier selective caching mechanism. In: IEEE 14th International Conference on Communication Technology (2012)
Hahn, S.S., Kim, J., Lee, S.: To collect or not to collect: just-in-time garbage collection for high-performance SSDs with long lifetimes (2015)
Lee, S., Liu, M., Jun, S., et al.: Application-managed flash. In: USENIX Conference on File and Storage Technologies. USENIX Association (2016)
Chen, Y.T., Yang, M.C., Chang, Y.H., et al.: KVFTL: optimization of storage space utilization for key-value-specific flash storage devices. In: 22nd Asia and South Pacific Design Automation Conference (ASP-DAC). IEEE (2017)
Zhang, J., Shu, J., Lu, Y.: ParaFS: a log-structured file system to exploit the internal parallelism of flash devices. In: USENIX (ATC 2016) (2016)
Bjørling, M., Madsen, J., Bonnet, P., Zuck, A., Bandic, Z., Wang, Q.: LightNVM: lightning fast evaluation platform for non-volatile memories (2014)
Microsoft-FAT-Specification. http://read.pudn.com/downloads77/ebook/294884/FAT32%20Spec%20%28SDA%20Contribution%29.pdf
Jiang, S., Zhang, L., Yuan, X.H., et al.: S-FTL: an efficient address translation for flash memory by exploiting spatial locality (2011)
Hu, X., Eleftheriou, E., Haas, R., Iliadis, I., Pletka, R.: Write amplification analysis in flashbased solid state drives. In: Proceedings of the Israeli Experimental Systems Conference (2009)
https://www.gamersnexus.net/guides/1157-ssd-controller-technology-overprovisioning-waf
Ziv, J., Lempel, A.: A universal algorithm for sequential data compression. IEEE Trans. Inf. Theory 23(3), 337–343 (1977)
Yim, K.S., Bahn, H., Koh, K.: A flash compression layer for SmartMedia card systems. IEEE Trans. Consum. Electron. 50(1), 192–197 (2004)
Feng, M., et al.: Big data analytics and mining for effective visualization and trends forecasting of crime data. IEEE Access 7, 106111–106123 (2019)
Gao, P., Ren, J.: Analysis and realization of Snort-based intrusion detection system. Comput. Appl. Softw. 23(8), 134–135 (2006)
Feng, W., Huang, W., Ren, J.: Class imbalance ensemble learning based on margin theory. Appl. Sci. 8(5), 815 (2018)
Sun, G., Ma, P., et al.: A stability constrained adaptive alpha for gravitational search algorithm. Knowl.-Based Syst. 139, 200–213 (2018)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Li, X., Zhai, Z., Ye, X., Dong, F. (2020). Partition Compression Flash Translation Layer Based on Data Separation. In: Ren, J., et al. Advances in Brain Inspired Cognitive Systems. BICS 2019. Lecture Notes in Computer Science(), vol 11691. Springer, Cham. https://doi.org/10.1007/978-3-030-39431-8_56
Download citation
DOI: https://doi.org/10.1007/978-3-030-39431-8_56
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-39430-1
Online ISBN: 978-3-030-39431-8
eBook Packages: Computer ScienceComputer Science (R0)