ALEX: Adaptive Log-Embedded Extent Layer for Low-Amplification SQLite Writes on Flash Storage
Source abstract
Abstract
Efficient metadata and page management are essential for sustaining database performance on modern flash-based storage. However, conventional SQLite configurations—rollback journal and WAL—often trigger excessive small writes and frequent synchronization events, leading to high write amplification and degraded tail latency, particularly on UFS and NVMe devices. This study introduces ALEX (Adaptive Log-Embedded Extent Layer), a lightweight VFS-level extension that coalesces scattered 4 KB page updates into sequential, page-aligned extents while embedding compact log records for recovery. The proposed design reduces redundant writes through in-memory page deduplication, minimizes fdatasync()frequency by flushing multi-page extents, and preserves full SQLite compatibility. We evaluate ALEX on both Linux NVMe SSDs and Android UFS storage under controlled workloads. Results show that ALEX significantly lowers write amplification, reduces sync counts, and improves p95–p99 write latency compared with baseline SQLite modes. The approach consistently achieves near-sequential write patterns without modifying SQLite internals. These findings demonstrate that lightweight extent-based coalescing can provide substantial efficiency gains for embedded and mobile database systems, offering a practical direction for enhancing SQLite performance on flash devices.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Advanced Data Storage Technologies · Distributed systems and fault tolerance · Cloud Data Security Solutions
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Smart Factory, Changshin University, Changwon-si 51352, Republic of Korea
Gyeongnam Digital Twin Research Center, Changwon-si 51352, Republic of Korea
Department of Computer Engineering, Daejin University, Pocheon-si 11159, Republic of Korea
Funding
Regional Innovation System & Education (RISE) program through the RISE Center, Gyeongsangnam-do · Ministry of Education · Gyeongsangnam-do Provincial Government, Republic of Korea
References (28)
Show source-provided references
1. Revisiting storage for smartphones
2. FlexHMB: A Flexible HMB Design Toward Bufferless Mobile Flash
3. An Efficient and Non-Time-Sensitive File-Aware Garbage Collection Algorithm for NAND Flash-Based Consumer Electronics10.1109/TCE.2018.2885102 ↗
4. Boosting User Experience via Foreground-Aware Cache Management in UFS Mobile Devices10.1109/TCAD.2020.3013078 ↗
5. Characterizing File Accesses in Android Applications and Caching Implications10.1109/ACCESS.2021.3125779 ↗
6. What’s on the Horizon? An In-Depth Forensic Analysis of Android and iOS Applications10.1109/ACCESS.2021.3095562 ↗
7. iAware: Interaction Aware Task Scheduling for Reducing Resource Contention in Mobile Systems10.1145/3609391 ↗
8. Improving Hybrid FTL by Fully Exploiting Internal SSD Parallelism with Virtual Blocks10.1145/2677160 ↗
9. A Real-Time Flash Translation Layer for NAND Flash Memory Storage Systems10.1109/TMSCS.2016.2516015 ↗
10. WiscKey: Separating Keys from Values in SSD-Conscious Storage10.1145/3033273 ↗
11. SCJ: Segment Cleaning Journaling for Log-Structured File Systems10.1109/ACCESS.2021.3121423 ↗
12. S-WAL: Fast and Efficient Write-Ahead Logging for Mobile Devices10.1109/TCE.2018.2859630 ↗
13. WAL-SSD: Address Remapping-Based Write-Ahead-Logging Solid-State Disks10.1109/TC.2019.2947897 ↗
14. In-memory write-ahead logging for mobile smart devices with NVRAM
15. Zhang, Y., Zhang, H., Cao, W., He, X., Park, D., Choi, J., and Park, S. (May, January 27). LazyBarrier: Reconstructing Android IO Stack for Barrier-Enabled Flash Storage. In Proceedings the of ASPLOS ’24, San Diego, CA, USA.
16. Liang, Y., Li, J., Ausavarungnirun, R., Pan, R., Shi, L., Kuo, T., and Xue, C.J. (2020, January 15–17). Acclaim: Adaptive Memory Reclaim to Improve User Experience in Android Systems. Proceedings of the 2020 USENIX ATC, Boston, MA, USA.
17. Choi, J., Hong, J., Kwon, Y.L., and Han, H. (2020, January 15–17). Libnvmmio: Reconstructing Software IO Path with Failure-Atomic Memory-Mapped Interface. Proceedings of the 2020 USENIX ATC, Boston, MA, USA.
18. Gaffney, K.P., Prammer, M., Brasfield, L., Hipp, D.R., Kennedy, D., and Patel, J.M. (2022, January 5–9). SQLite: Past, present, and future. Proceedings of the VLDB Endowment, Sydney, Australia.10.14778/3554821.3554842 ↗
19. Lee, C., Sim, D., Hwang, J.Y., and Cho, S. (2015, January 16–19). F2FS: A New File System for Flash Storage. Proceedings of the 2015 USENIX FAST, Santa Clara, CA, USA.
20. The design and implementation of a log-structured file system10.1145/146941.146943 ↗
21. Chan, H.H.W., Li, Y., Lee, P.P.C., and Xu, Y. (2018, January 11–13). HashKV: Enabling Efficient Updates in KV Storage via Hashing. Proceedings of the 2018 USENIX ATC, Boston, MA, USA.
22. Maximizing the user experience with energy-based fair sharing in battery limited mobile systems10.1109/TCE.2013.6626257 ↗
23. Improving the SSD Performance by Exploiting Request Characteristics and Internal Parallelism10.1109/TCAD.2017.2697961 ↗
24. Maneas, S., Mahdaviani, K., Emami, T., and Schroeder, B. (2020, January 24–27). A Study of SSD Reliability in Large Scale Enterprise Storage Deployments. Proceedings of the 2020 USENIX FAST, Santa Clara, CA, USA.
25. Error Characterization, Mitigation, and Recovery in Flash-Memory-Based Solid-State Drives10.1109/JPROC.2017.2713127 ↗
26. Hahn, S.S., Lee, S., Ji, C., Chang, L., Yee, I., Shi, L., Xue, C.J., and Kim, J. (2017, January 12–14). Improving File System Performance of Mobile Storage Systems Using a Decoupled Defragmenter. Proceedings of the 2017 USENIX ATC, Santa Clara, CA, USA.
27. Understanding intrinsic characteristics and system implications of flash memory based solid state drives10.1145/2492101.1555371 ↗
28. Improving Performance for Flash-Based Storage Systems through GC-Aware Cache Management10.1109/TPDS.2017.2692757 ↗