An On-Line Reorganization Framework for SAN File Systems

  • Shahram Ghandeharizadeh
  • Shan Gao
  • Chris Gahagan
  • Russ Krauss
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4152)


While the cost per megabyte of magnetic disk storage is economical, organizations are alarmed by the increasing cost of managing storage. Storage Area Network (SAN) architectures strive to minimize this cost by consolidating storage devices. A SAN is a special-purpose network that interconnects different data storage devices with servers. While there are many definitions for a SAN, there is a general consensus that it provides access at the granularity of a block and is typically used for database applications.

In this study, we focus on SAN switches that include an embedded storage management software in support of virtualization. We describe an On-line Re-organization Environment, ORE, that controls the placement of data to improve the average response time of the system. ORE is designed for a heterogeneous collection of storage devices. Its key novel feature is its use of “time” to quantify the benefit and cost of a migration. It migrates a fragment only when its net benefit exceeds a pre-specified threshold. We describe a taxonomy of techniques for fragment migration and employ a trace driven simulation study to quantify their tradeoff. Our performance results demonstrate a significant improvement in response time (order of magnitude) for those algorithms that employ ORE’s cost/benefit feature. Moreover, a technique that employs bandwidth of all devices intelligently is superior to one that simply migrates data to the fastest devices.


Time Slice Disk Drive Average Response Time Embed Device Disk Array 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Amiri, K., Gibson, G., Golding, R.: Highly Concurrent Shared Storage. In: Proceedings of the International Conference on Distributed Computing Systems (April 2000)Google Scholar
  2. 2.
    Amiri, K., Petrou, D., Ganger, G., Gibson, G.: Dynamice Function Placement for Data-Intensive Cluster Ccomputing. In: Proceedings of the USENIX Annual Technical Conference (June 2000)Google Scholar
  3. 3.
    Anderson, T., Breitbart, Y., Korth, H., Wool, A.: Replication, Consistency, and Practicality: Are These Mutually Exclusive?. In: Proceedings of ACM SIGMOD p. 27 (1998)Google Scholar
  4. 4.
    Aref, W., Kamel, I., Niranjan, T., Ghandeharizadeh, S.: Disk Scheduling for Displaying and Recording Video in Non-Linear News Editing Systems. In: Proceedings of Multimedia Computing and Networking Conference (1997)Google Scholar
  5. 5.
    Arpaci-Dusseau, R.H., Anderson, E., Treuhaft, N., Culler, D.E., Hellerstein, J.M., Patterson, D., Yelick, K.: Cluster I/O with River: Making the Fast Case Common. In: Proceedings of the Sixth Workshop on Input/Output in Parallel and Distributed Systems, Atlanta, GA, pp. 10–22. ACM Press, New York (1999)CrossRefGoogle Scholar
  6. 6.
    Berson, S., Ghandeharizadeh, S., Muntz, R., Ju, X.: Staggered Striping in Multimedia Information Systems. In: Proceedings of ACM SIGMOD, pp. 79–90 (1994)Google Scholar
  7. 7.
    Chen, P.M., Patterson, D.A.: Maximizing Performance in a Striped Disk Array. In: Proc. 17th Annual Int’l Symp. on Computer Architecture, ACM SIGARCH Computer Architecture News, p. 322 (1990)Google Scholar
  8. 8.
    Copeland, G., Alexander, W., Boughter, E., Keller, T.: Data placement in Bubba. In: Proceedings of ACM SIGMOD, pp. 99–108 (1988)Google Scholar
  9. 9.
    Dan, A., Sitaram, D.: An Online Video Placement Policy Based on Bandwidth to Space Ratio (BSR). In: Proceedings of ACM SIGMOD, pp. 376–385 (1995)Google Scholar
  10. 10.
    DeWitt, D., Gray, J.: Parallel Database Systems: The Future of High Performance Database Systems. Communications of the ACM 35(6), 85–98 (1992)CrossRefGoogle Scholar
  11. 11.
    Drapeau, A.L., Shirrif, K.W., Hartman, J.H., Miller, E.L., Seshan, S., Katz, R.H., Lutz, K., Patterson, D.A., Lee, E.K., Chen, P.H., Gibson, G.A.: RAID-II: A high-bandwidth network file server. In: Proceedings of the 21st Annual International Symposium on Computer Architecture, pp. 234–244 (1994)Google Scholar
  12. 12.
    Ghandeharizadeh, S., Ierardi, D., Kim, D.: Placement of Data in Multi Zone Disk Drives. In: Proceedings of the Second International Baltic Workshop on Databases and Information Systems (1996)Google Scholar
  13. 13.
    Ghandeharizadeh, S., Ierardi, D., Zimmermann, R.: An Algorithm for Disk Space Management to Minimize Seeks. The Computer Journal 57, 75–81 (1996)MATHGoogle Scholar
  14. 14.
    Ghandeharizadeh, S., Ierardi, D., Zimmermann, R.: Management of Space in Hierarchical Storage Systems. In: Arbib, M., Grethe, J. (eds.) A Guide to Neuroinformatics. Academic Press, London (2001)Google Scholar
  15. 15.
    Ghandeharizadeh, S., Kim, S., Shi, W., Zimmermann, R.: On minimizing startup latency in scalable continuous media servers. Multimedia Computing and Networking (February 1997)Google Scholar
  16. 16.
    Gibson, G.: Redundant Disk Arrays: Reliable, Parallel Secondary Storage (1991)Google Scholar
  17. 17.
    Gibson, G.A., Patterson, D.A.: Designing Disk Arrays for High Data Reliability. Journal of Parallel and Distributed Computing 17(1–2), 4–27 (1993)CrossRefGoogle Scholar
  18. 18.
    Golubchik, L., Muntz, R.R.: Fault Tolerance Issues in Data Declustering for Parallel Database Systems. Data Engineering Bulletin 17(3), 14–28 (1994)Google Scholar
  19. 19.
    Gray, J., Graefe, G.: The 5 Minute Rule, Ten Years Later. In: SIGMOD Record, vol. 26 (1997)Google Scholar
  20. 20.
    Gray, J., Helland, P., O’Neil, P., Shasha, D.: The Dangers of Replication and a Solution. In: Proceedings of ACM SIGMOD, pp. 173–182 (1996)Google Scholar
  21. 21.
    Gray, J., Horst, B., Walker, M.: Parity Striping of Disk Arrays: Low Cost Reliable Storage with Acceptable Throughput. In: Proceedings of the VLDB Conference, pp. 152–162 (September 1990)Google Scholar
  22. 22.
    Gray, J., Reuter, A.: Transaction Processing: Concepts and Techniques. Morgan Kaufmann, San Francisco (1992)Google Scholar
  23. 23.
    Hsiao, H., DeWitt, D.: Chained Declustering: A New Availability Strategy for Multiprocessor Database Machines. In: Proceedings of 6th International Data Engineering Conference, pp. 456–465 (1990)Google Scholar
  24. 24.
    Lakhamraju, M.K., Rastogi, R., Seshadri, S., Sudarshan, S.: On-Line Reorganization in Object Databases. In: Proceedings of ACM SIGMOD, pp. 58–69 (2000)Google Scholar
  25. 25.
    Lee, E.K., Thekkath, C.A.: Petal: Distributed Virtual Disks. In: Proceedings of the Seventh International Conference on Architectural Support for Programming Languages and Operating Systems, Cambridge, MA, pp. 84–92 (1996)Google Scholar
  26. 26.
    Lee, M.L., Kitsuregawa, M., Ooi, B.C., Tan, K., Mondal, A.: Towards Self-tuning Data Placement in Parallel Database Systems. In: Proceedings of ACM SIGMOD, pp. 225–236 (2000)Google Scholar
  27. 27.
    Petrou, D., Amiri, K., Ganger, G., Gibson, G.: Easing the Management of Data-Parallel Systems via Adaptation. In: Proceedings of the 9th ACM SIGOPS European Workshop (September 2000)Google Scholar
  28. 28.
    Scheuermann, P., Weikum, G., Zabback, P.: “Disk Cooling” in Parallel Disk Systems. Data Engineering Bulletin 17(3), 29–40 (1994)Google Scholar
  29. 29.
    Scheuermann, P., Weikum, G., Zabbak, P.: Data Partitioning and Load Balancing in Parallel Disk Systems. VLDB Journal 7(1) (1998)Google Scholar
  30. 30.
    Siewiorek, D.P., Swarz, R.S.: The Theory and Practice of Reliable System Design. Digital Press (1982)Google Scholar
  31. 31.
    Veitch, A., Riedel, E., Towers, S., Wilkes, J.: Towards Global Storage Management and Data Placement. Technical Report HPL-SSP-2001-1, Hewlett Packard Laboratories (March 2001)Google Scholar
  32. 32.
    Vingralek, R., Breitbart, Y., Weikum, G.: Snowball: Scalable Storage on Networks of Workstations with Balanced Load. Distributed and Parallel Databases 6(2), 117–156 (1998)CrossRefGoogle Scholar
  33. 33.
    Weikum, G., Hasse, C., Moenkeberg, A., Zabback, P.: The COMFORT Automatic Tuning Project, Invited Project Review. Information Systems 19(5), 381–432 (1994)CrossRefGoogle Scholar
  34. 34.
    Wiesmann, M., Pedone, F., Schiper, A., Kemme, B., Alonso, G.: Understanding Replication in Databases and Distributed Systems. In: Proceedings of 20th International Conference on Distributed Computing Systems (ICDCS 2000), Taipei, Taiwan, R.O.C., pp. 264–274. IEEE Computer Society Press, Los Alamitos (2000)Google Scholar
  35. 35.
    Wilkes, J., Golding, R., Staelin, C., Sullivan, T.: The HP AutoRAID Hierarchical Storage System. In: Proceedings of the Fifteenth ACM Symposium on Operating Systems Principles, Copper Mountain, CO, pp. 96–108. ACM Press, New York (1995)CrossRefGoogle Scholar
  36. 36.
    Wu, K., Yu, P., Chung, J., Teng, J.: A Performance Study of Workfile Disk Management for Concurrent Mergesorts in a Multiprocessor Database System. In: Proceedings of the VLDB Conference, September 1995, pp. 100–110 (1995)Google Scholar
  37. 37.
    Yu, X., Gum, B., Chen, Y., Wang, R., Li, K., Krishnamurthy, A., Anderson, T.: Trading Capacity for Performance in a Disk Array. In: Symposium on Operating Systems Design and Implementation (October 2000)Google Scholar
  38. 38.
    Zimmermann, R., Ghandeharizadeh, S.: HERA: Heterogeneous Extension of RAID. In: Proceedings of the International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA 2000) (June 2000)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Shahram Ghandeharizadeh
    • 1
  • Shan Gao
    • 1
  • Chris Gahagan
    • 2
  • Russ Krauss
    • 2
  1. 1.Department of Computer ScienceUniversity of Southern CaliforniaLos AngelesUSA
  2. 2.BMC Software Inc.HoustonUSA

Personalised recommendations