Transparent online storage compression at the block-level

ACM Transactions on Storage

Volumn 8, Issue 2, 2012, Pages

  Klonatos, Yannis ^a,b   Makatos, Thanos ^a   Marazakis, Manolis ^a   Flouris, Michail D ^a   Bilas, Angelos ^a,b  

^a INSTITUTE OF COMPUTER SCIENCE   (Greece)

^b UNIVERSITY OF CRETE   (Greece)

Author keywords

Block level compression; SSD based I O cache

Indexed keywords

BLOCK ALLOCATION; CASE-STUDIES; CPU UTILIZATION; CURRENT TECHNOLOGY; DISK-BASED; I/O LATENCY; I/O PERFORMANCE; IN-LINE; LINUX KERNEL; MULTI CORE; SIGNIFICANT IMPACTS; SPACE EFFICIENCIES; SSD-BASED I/O CACHE; STORAGE CACHES; STORAGE CAPACITY; STORAGE SYSTEMS; WORK SCHEDULING;

EFFICIENCY; METADATA; PROGRAM PROCESSORS; VIRTUAL STORAGE;

ONLINE SYSTEMS;

EID: 84863607148     PISSN: 15533077     EISSN: 15533093     Source Type: Journal    
DOI: 10.1145/2180905.2180906     Document Type: Article

References (57)

1. ADAPTEC, INC. 2009. MaxIQ SSD cache performance. White paper. www.adaptec.com/en-US/products/CloudComputing/-MaxIQ/SSD-Cache-Performance/ index.htm.
2. AGRAWAL, N, PRABHAKARAN, V., WOBBER, T., DAVIS, J. D., MANASSE, M., and PANIGRAHY, R. 2008. Design tradeoffs for SSD performance. In Proceedings of the USENIX Annual Technical Conference (ATC). 57-70.
3. ALEPH ONE LTD, EMBEDDED DEBIAN. 2002. Yaffs: A NAND-Flash Filesystem.
4. APPEL, A. W. and LI, K. 1991. Virtual memory primitives for user programs. SIGPLAN Notes 26, 4, 96-107. (Pubitemid 21702164)
5. AYERS, L. 1997. E2compr: Transparent file compression for Linux. http://e2compr.sourceforge.net/.
6. BOBBARJUNG, D. R., JAGANNATHAN, S., and DUBNICKI, C. 2006. Improving duplicate elimination in storage systems. Trans. Storage 2, 4, 424-448. (Pubitemid 46192923)
7. BURROWS, M., JERIAN, C, LAMPSON, B., and MANN, T. 1992. On-line data compression in a logstructured file system. In Proceedings of the 5th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS'92). ACM, New York, 2-9. (Pubitemid 23642269)
8. CATE, V. and GROSS, T. 1991. Combining the concepts of compression and Caching for two-level filesystem. In Proceedings of the 4th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS'91). ACM, New York, 200-211. (Pubitemid 21702155)
9. COFFING, C. and BROWN, J. H. 1997. A survey of modern file compression techniques. http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.50.9847.
10. CORMACK, G. V. 1985. Data compression on a database system. Comm. ACM 28, 12, 1336-1342.
11. DEUTSCH, L. P. and GAILLY, J.-L. 1996. ZLIB Compressed Data Format Specification version 3.3. Internet RFC 1950.
12. DIRIK, C. and JACOB, B. 2009. The performance of PC solid-state disks (SSDs) as a function of bandwidth, concurrency, device architecture, and system organization. In Proceedings of the ISCA09. ACM, 279-289.
13. DOUGLIS, F. 1992. On the role of compression in distributed systems. In Proceedings of the ACM SIGOPS, EW 5. 1-6.
14. DOUGLIS, F. 1993. The compression cache: Using on-line compression to extend physical memory. In Proceedings of the Winter USENIX Conference. 519-529.
15. ENGEL, J. and MERTENS, R. 2006. LogFS - finally a scalable flash file system. http://lazybastard.org/joern/logfs 1.pdf
16. FUSION-IO. 2007. Fusion-IO's solid state storage: A new standard for enterprise-class reliability. http://www.fusionio.com.
17. GUPTA, N. 2010. Compcache: Compressed in-memory swap device for Linux. http://code.google.com/p/compcache.
18. KATCHER, J. 1997. PostMark: A new file system benchmark. http://www.netapp. com/tech-library/3022.html.
19. KGIL, T. and TREVOR, M. 2006. Flashcache: A NAND flash memory file cache for low power web servers. In Proceedings of the CASES'06. ACM, 103-112. (Pubitemid 47113099)
20. KIM, H. and AHN, S. 2008. BPLRU A buffer management scheme for improving random writes in flash storage. In Proceedings of the 6th USENIX Conference on File and Storage Technologies (FAST'08). USENIX Association, Berkeley, CA, 1-14.
21. LEE, S.-W., MOON, B., PARK, C, KIM, J.-M., and KIM, S.-W. 2008. A case for flash memory SSD in enterprise database applications. In Proceedings of the ACM SIGMOD International Conference on Management of Data (SIGMOD'08). ACM, New York, 1075-1086.
22. LELEWER, D. A. and HIRSCHBERG, D. S. 1987. Data compression. ACMComput. Surv. 19, 3, 261-296.
23. LEVENTHAL, A. 2008. Flash storage memory. Comm. ACM 51, 7, 47-51.
24. LOUGHER, P. and LOUGHER, R. 2008. SquashFS. http://squashfs.sourceforge. net.
25. MAKATOS, T, KLONATOS, Y., MARAZAKIS, M., FLOURIS, M. D., and BILAS, A. 2010a. Using transparent compression to improve SSD-based I/O caches. In Proceedings of the 5th European Conference on Computer Systems (EuroSys'10). ACM, New York, NY, 1-14.
26. MAKATOS, T, KLONATOS, Y., MARAZAKIS, M., FLOURIS, M. D., and BILAS, A. 2010b. ZBD: Using transparent compression at the block level to increase storage space efficiency In Proceedings of the IEEE International Workshop on Storage Network Architecture and Parallel I/Os. 61-70.
27. MANBER, U. 1994. Finding similar files in a large file system. In Proceedings of the USENIX Winter 1994 Technical Conference (WTEC'94). USENIX Association, 2-2.
28. MEISNER, D., GOLD, B. T., and WENISCH, T. F. 2009. POWERNAP: Eliminating server idle power. In Proceedings of the 14th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS'09). ACM, New York, 205-216.
29. MICROSOFT CORPORATION. 2008. Understanding NTFS Compression. http://blogs.msdn. com/ntdebugging/archive/2008/05/20/-understanding-ntfs- compression. aspx.
30. MICROSOFT CORPORATION. 2009. Best practices for NTFS compression in Windows. support.microsoft.com/default.aspx?scid=kb;en-us;Q251186.
31. MICROSOFT CORPORATION. 2010. Explore the features: Windows ReadyBoost. www.microsoft.com/windows/windows-vista/features/readyboost.aspx.
32. NARAYANAN, D., THERESKA, E., DONNELLY, A., ELNIKETY, S., and ROWSTRON, A. 2009. Migrating server storage to SSDS: Analysis of tradeoffs. In Proceedings of the 4th ACM European Conference on Computer Systems (EuroSys'09). ACM, New York, 145-158.
33. NG, W. K. and RAVISHANKAR, C. V. 1997. Block-oriented compression techniques for large statistical databases. IEEE Trans. Knowl. Data Eng. 9, 2, 314-328. (Pubitemid 127763274)
34. NORTH AMERICAN SYSTEMS INTERNATIONAL, INC. FalconStor HotZone - Maximize the performance of your SAN. http://www.nasi.com/hotZone.php.
35. OBERHUMER, M. F. X. J. 2008. LZO-A real-time data compression library. http://www.oberhumer.com/opensource/lzo/.
36. ORACLE CORPORATION AND SUN MICROSYSTEMS, INC. 2009. Oracle Solaris ZFS. http://www.oracle.com/us/products/servers-storage/storage/storage-software/ 031857.htm.
37. POESS, M. and POTAPOV, D. 2003. Data compression in oracle. In Proceedings of the 29th VLDB Conference.
38. RAJIMWALE, A., PRABHAKARAN, V., and DAVIS J. D. 2009. Block management in solid-state devices. In Proceedings of the USENIX Annual Technical Conference.
39. RIZZO, L. 1997. A very fast algorithm for RAM compression. SIGOPS Oper. Syst. Rev. 31, 2, 36-45. (Pubitemid 127465451)
40. ROSENBLUM, M. and OUSTERHOUT, J. K. 1992. The design and implementation of a log-structured file system. ACM Trans. Comput. Syst. 10, 1, 26-52. (Pubitemid 23598979)
41. RUSSEL, P. 2002. The compressed loopback device. http://www.knoppix.net/ wiki/Cloop.
42. SAVAGE, S. 2006. CBD compressed block device, new embedded block device. http://lwn. net/Articles/168725.
43. SMITH, M. E. G. and STORER, J. A. 1985. Parallel algorithms for data compression. J. ACM 32, 2, 344-373.
44. SPEC. 2008a. SPECsfs2008: SPEC's benchmark designed to evaluate the speed and request-handling capabilities of file servers utilizing the NFSv3 and CIFS protocols. http://www.spec.org/sfs2008/.
45. SPEC. 2008b. SPECsfs2008-cifs published results, as of Nov-10-2009. http://www.spec.org/sfs2008/results/-sfs2008.html.
46. SPEC. 2009. 6SPECmail2009 published results, as of Nov-06-2009. http://www.spec.org/mail2009/results/-specmail-ent2009.html.
47. SVOBODA, M. 2010. FuseCompress, a mountable Linux file system which transparently compress its content. http://miio.net/wordpress/projects/ fusecompress/.
48. THOMAS, C. and WONG, M. 2007. Database Test 2 (DBT-2), an OLTP transactional performance test. http://osdldbt.sourceforge.net/.
49. TPC. 1997. Overview of the TPC benchmark C: The order-entry benchmark. http://www.tpc.org/tpcc/default.asp.
50. TPC. 2009a. Top ten non-clustered TPC-H published results by performance. http://tpc.org/tpch/results/tpch-perf-results.asp?resulttype=noncluster.
51. TPC. 2009b. TPC-H: An ad-hoc, decision support benchmark. www.tpc.org/tpch.
52. WELCH, T A. 1984. A technique for high-performance data compression. IEEE Computer 17, 6, 8-19.
53. WILSON, P. R., KAPLAN, S. F., and SMARAGDAKIS, Y. 1999. The case for compressed caching in virtual memory systems. In Proceedings of the USENIX Annual Technical Conference. USENIX Association, 101-116.
54. WOODHOUSE, D. 2001. JFFS: The Journalling Flash File System. http://www.csie.nctu.edu.tw/-ijsung/documents/jffs2.pdf
55. YANG, L., DICK, R. P., LEKATSAS, H., and CHAKRADHAR, S. 2005. Crames: Compressed ram for embedded systems. In Proceedings of the 3rd IEEE/ACM/IFIP International Conference on Hardware/Software Codesign and System Synthesis (CODES+ISSS'05). ACM, New York, 93-98. (Pubitemid 41551291)
56. ZHU, B., LI, K., and PATTERSON, H. 2008. Avoiding the disk bottleneck in the data domain deduplication file system. In Proceedings of the 6th USENIX Conference on File and Storage Technologies (FAST'08). USENIX Association, Berkeley, CA, 1-14.
57. ZIV, J. and LEMPEL, A. 1977. A universal algorithm for sequential data compression. IEEE Trans. Inf. Theory 23, 337-343.