Adaptive Sequential Prefetching for Multiple Streams

  • Yong Li
  • Dan Feng
  • Zhan Shi
  • Qing Liu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7901)


Modern storage systems are becoming increasingly consolidated. As a result, there exists a competition for resources among concurrent streams. Sequential prefetching is widely used in modern storage system. Most of them always ignore the impact of diversified access rate of concurrent streams. However the concurrent streams with diversified access rate will introduce several problems. The streams with fast access rate may evict the cache blocks of the streams with slow access rate and lead the slow streams re-fetch the evicted cache blocks in future access, which makes the prefetching wastage and unfairness to the slow streams. We design and implement a novel, adaptive algorithm, named ASPM to solve these problems. Our experiments show that, compared with LRU and AMP, ASPM can achieve significantly improvement in fairness among concurrent streams and slightly in performance (average on 6.8%).


sequential prefetching adaptive storage system 


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  1. 1.
    Carr, R.W., Hennessy, J.L.: WSCLOCK-a simple and effective algorithm for virtual memory management. SIGOPS Oper. Syst. Rev. 15, 87–95 (1981)CrossRefGoogle Scholar
  2. 2.
    O’Neil, E.J., O’Neil, P.E., Weikum, G.: The LRU-K page replacement algorithm for database disk buffering. SIGMOD Rec. 22, 297–306 (1993)CrossRefGoogle Scholar
  3. 3.
    O’Neil, E.J., O’Neil, P.E., Weikum, G.: An optimality proof of the LRU-K page replacement algorithm. J. ACM 46, 92–112 (1999)MathSciNetzbMATHCrossRefGoogle Scholar
  4. 4.
    Jiang, S., Zhang, X.: LIRS: an efficient low inter-reference recency set replacement policy to improve buffer cache performance. SIGMETRICS Perform. Eval. Rev. 30, 31–42 (2002)CrossRefGoogle Scholar
  5. 5.
    Zhou, Y., Philbin, J., Li, K.: The Multi-Queue Replacement Algorithm for Second Level Buffer Caches. In: Proceedings of the General Track: 2002 USENIX Annual Technical Conference, pp. 91–104. USENIX Association (2001)Google Scholar
  6. 6.
    Li, Z., Chen, Z., Srinivasan, S.M., Zhou, Y.: C-Miner: mining block correlations in storage systems. In: Proceedings of the 3rd USENIX Conference on File and Storage Technologies, p. 13. USENIX Association, San Francisco (2004)Google Scholar
  7. 7.
    Gill, B.S., Modha, D.S.: SARC: sequential prefetching in adaptive replacement cache. In: Proceedings of the Annual Conference on USENIX Annual Technical Conference, p. 33. USENIX Association, Anaheim (2005)Google Scholar
  8. 8.
    Gill, B.S., Bathen, L.A.D.: AMP: adaptive multi-stream prefetching in a shared cache. In: Proceedings of the 5th USENIX Conference on File and Storage Technologies, p. 26. USENIX Association, San Jose (2007)Google Scholar
  9. 9.
    Zhang, Z., Kulkarni, A., Ma, X., Zhou, Y.: Memory resource allocation for file system prefetching: from a supply chain management perspective. In: Proceedings of the 4th ACM European Conference on Computer Systems, pp. 75–88. ACM, Nuremberg (2009)CrossRefGoogle Scholar
  10. 10.
    Bucy, J.S., Schindler, J., Schlosser, S.W., Ganger, G.R., Contributors: The DiskSim simulation environment version 4.0 reference manual (2008)Google Scholar
  11. 11.
    Lab, O.S.D.: Iometer I/O performance analysis tool (2003)Google Scholar
  12. 12.
    Axboe, J., Brunelle, A.D., Scott, N.: blktrace(8) - linux man page (2013)Google Scholar
  13. 13.
    Li, M., Varki, E., Bhatia, S., Merchant, A.: TaP: table-based prefetching for storage caches. In: Proceedings of the 6th USENIX Conference on File and Storage Technologies, pp. 1–16. USENIX Association, San Jose (2008)Google Scholar
  14. 14.
    Liang, S., Jiang, S., Zhang, X.: STEP: Sequentiality and Thrashing Detection Based Prefetching to Improve Performance of Networked Storage Servers. In: Proceedings of the 27th International Conference on Distributed Computing Systems, p. 64. IEEE Computer Society (2007)Google Scholar
  15. 15.
    Patterson, R.H., Gibson, G.A., Ginting, E., Stodolsky, D., Zelenka, J.: Informed prefetching and caching. SIGOPS Oper. Syst. Rev. 29, 79–95 (1995)CrossRefGoogle Scholar
  16. 16.
    Wachs, M., Abd-El-Malek, M., Thereska, E., Ganger, G.R.: Argon: performance insulation for shared storage servers. In: Proceedings of the 5th USENIX Conference on File and Storage Technologies, p. 5. USENIX Association, San Jose (2007)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Yong Li
    • 1
  • Dan Feng
    • 1
  • Zhan Shi
    • 1
  • Qing Liu
    • 1
  1. 1.School of Computer, Division of Data Storage System, Wuhan National Lab for OptoelectronicsHuazhong University of Science and TechnologyWuhanChina

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