當應用程式需要高I/O 的性能，相對於傳統的硬碟，固態硬碟可以提供更好的效能。因此，像資料庫系統這種需要高I/O 的性能的，可以藉由將經常被使用的資料搬移到固態硬碟上來去提升其效能。但是，固態硬碟在單位價格上比傳統硬碟貴上許多。所以我們需要決定哪些資料被放置在固態硬碟，哪些需要被放置在傳統硬碟上。
在我們的論文裡，我們提出一個針對資料庫系統的一個基於優先權資料管理方法在使用固態硬碟下。這個方法可以藉由放置高優先權資料到固態硬碟上和放置低優先權的資料到傳統硬碟上去提升資料庫系統的效能。我們將做實驗去說明我們所提出的方法可以達到此目標，在使用少量的固態硬碟空間下。

When some applications require high I/O performance, SSDs (solid-state drives) can be used because of its better performance than traditional HDDs (hard-disk drives). Therefore,the response time of a database system can be improved by moving data that are frequently accessed to the SSDs. Because the SSD space is limited and more expansive than the HDD space, we need to determine which appropriate data are migrated between the SSDs and the HDDs. In the thesis, we will propose a priority-based data management method for databases using solid state drives. The proposed method can provide database systems with high I/O performance by moving the high-priority data to the SSDs with the fast access property and the low-priority data to the HDDs with the low cost. The experimental results also show that the proposed method with a small amount of the SSD space can achieve the goal.

[1] M. Canim, G. A. Mihaila, B. Bhattacharjee, K. A. Ross, and C. A. Lang, “An object placement advisor for db2 using solid state storage,” in Proceedings of the VLDB Endowment, vol. 2, pp. 1318–1329, Aug 2009.
[2] M. Mehta and D. J. DeWitt, “Data placement in shared-nothing parallel database
systems,” in The VLDB Journal —The International Journal on Very Large Data Bases, vol. 6, pp. 53–72, February 1997.
[3] M. Canim, G. A. Mihaila, B. Bhattacharjee, K. A. Ross, and C. A. Lang, “Ssd bufferpool extensions for database systems,” in Proceedings of the VLDB Endowment, vol. 3, pp. 1435–1446, September 2010.
[4] J. Schindler, A. Ailamaki, and G. R. Ganger, “Matching database access patterns to storage characteristics,” in In FAST ’02:Proceedings of the 1st USENIX Conference on Fileand Storage Technologies, p. 22, 2002.
[5] Oracle, “Take the guesswork out of database layout and i/o tuning with automatic storage management,” in Oracle Technical White Paper, December 2005.
[6] A. Sachedina, M. Huras, and A. Colangelo, “Best practices database storage,” in White paper, IBM DB2 for Linux, UNIX, and Windows, Oct 2008.
[7] B. H. Bloom, “Space/time trade-offs in hash coding with allowable errors,” in Commun.ACM, vol. 13(7), pp. 422–426, July 1970.
[8] Y. Lv, B. Cui, X. Chen, and J. Li, “Hotness-aware buffer management for flashbased hybrid storage systems,” in Mass Storage Systems and Technologies (MSST),pp. 1631–1636, Oct 2013.
[9] D. Park, Y. J. Nam, B. Debnath, D. H. C. Du, Y. Kim, and Y. Kim, “An on-line hot data identification for flash-based storage using sampling mechanism,” in White paper, IBM DB2 for Linux, UNIX, and Windows, vol. 13, pp. 51–64, March 2013.
[10] J.-W. Hsieh, T.-W. Kuo, and L.-P. Chang, “Efficient identification of hot data for flash memory storage systems,” in Proceedings of the VLDB Endowment, vol. 2,pp. 22–40, February 2006.
[11] D. Park and D. H. Du, “Hot data identification for flash-based storage systems using multiple bloom filters,” in Mass Storage Systems and Technologies (MSST), pp. 1–11, May 2011.
[12] “Performance value of solid state drives using ibm i,” May 2009. http://www-03.ibm.com/systems/resources/ssd_ibmi.pdf.
[13] N. Roussopoulos, “Materialized views and data warehouses,” vol. 27, pp. 21–26,March 1998.
[14] J. Goldstein and P. Ake Larson, “Optimizing queries using materialized views: a practical, scalable solution,” vol. 30, pp. 331–342, June 2001.
[15] A. Katsifodimos, I. Manolescu, and V. Vassalos, “Materialized view selection for xquery workloads,” pp. 565–576, May 2012.
[16] C. Zhu, Q. Zhu, C. Zuzarte, and W. Ma, “A materialized-view based technique to optimize progressive queries via dependency analysis,” pp. 60–73, November 2011.
[17] C. L. Liu and J. W. Layland, “Scheduling algorithms for multiprogramming in a hard real-time environment,” in J. ACM, vol. 20, pp. 46–61, Jan 1973.
[18] L. Sha, R. Rajkumar, and J. Lehoczky, “Priority inheritance protocols: an approach to real-time synchronization,” in Computers, IEEE Transactions, vol. 39, pp. 1175–1185, Sep 1990.
[19] “Flashcache.” https://github.com/facebook/flashcache.
[20] “B-cache.” http://bcache.evilpiepirate.org/.
[21] “Tpc-h, decision support benchmark..” http://www.tpc.org/tpch/.