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MCB: a multidevice cooperative buffer management strategy for boosting the write performance of the SSD-SMR hybrid storage

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Abstract

Shingled magnetic recording (SMR) disks satisfy the growing demand for storage capacity for big data applications with their high capacity and low cost. However, the most severe challenge for SMR disks is the precipitous degradation of I/O performance when subjected to non-sequential writes. Using Solid State Drives (SSDs) as external caches for SMR disks is a cost-effective method to improve the I/O performance of SMR disks. Nevertheless, the existing SMR-oriented cache replacement algorithm is ineffective in resolving the conflict between the write amplification and the cache hit rate, resulting in limited performance gains from SSDs to SMR disks. In this paper, we design a multidevice cooperative buffer (MCB) management strategy to boost the write performance of SSD-SMR storage systems. Firstly, MCB selectively directs write traffic into the SSD cache to reduce the frequency of cleaning activity. Then, MCB adaptively evicts victim blocks from the SSD cache based on the locality principle. Finally, MCB utilizes a novelty SMR disk internal persistent buffer management mechanism to further optimize the efficiency of the SSD cache cleaning. The experimental results show that MCB achieves 7.4\(\times\) and 1.5\(\times\) performance improvements for write-intensive traces with spatial locality and temporal locality, respectively, compared to the state-of-the-art strategies.

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Notes

  1. The manufacturer packs a certain number of tracks on the disk surface into bands/zones, which prevents the propagation of write amplification caused by sectors updates.

  2. A set of blocks in a cache/buffer that belongs to the same zone is treated as a cluster. When a cache/buffer replacement occurs, the victim cluster is written back to the native storage area.

  3. The cleaning activity of the current cache/buffer causes the cleaning activity of the next-level buffer to be triggered, which may cause the user I/O requests to be blocked for a long time.

  4. The timestamp is self-increasing as the number of I/O requests accumulates.

  5. A hot read block is one where the last access to the block was a read request, and where the read frequency is greater than the write frequency.

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Acknowledgements

This work was supported in part by the National Natural Science Foundation of China (61972311, 62002279) and in part by the Shandong Provincial Natural Science Foundation under Grant (ZR2021LZH009).

Funding

This work was supported in part by the National Natural Science Foundation of China (61972311, 62002279), in part by the Shandong Provincial Natural Science Foundation under Grant (ZR2021LZH009).

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Author notes

  1. Shiqiang nie, Jinyu Wang and Song Liu contributed equally to this work.

Authors and Affiliations

  1. School of Computer Science and Technology, Xi’an Jiaotong University, West Xianning Road, Xi’an, 710049, Shaanxi, China

    Chi Zhang, Shiqiang Nie, Jinyu Wang, Song Liu & Weiguo Wu

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  1. Chi Zhang
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Contributions

CZ: Conceptualization, Methodology, Software, Investigation, Writing—original draft, Writing—review and editing, Validation. SN: Investigation. JW: Formal analysis. SL: Data curation. WW: Resources, Funding acquisition, Project administration, Supervision.

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Correspondence to Weiguo Wu.

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Zhang, C., Nie, S., Wang, J. et al. MCB: a multidevice cooperative buffer management strategy for boosting the write performance of the SSD-SMR hybrid storage. J Supercomput 79, 13462–13489 (2023). https://doi.org/10.1007/s11227-023-05201-7

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