Declustering Two-Dimensional Datasets over MEMS-Based Storage
Due to the large difference between seek time and transfer time in current disk technology, it is advantageous to perform large I/O using a single sequential access rather than multiple small random I/O accesses. However, prior optimal cost and data placement approaches for processing range queries over two-dimensional datasets do not consider this property. In particular, these techniques do not consider the issue of sequential data placement when multiple I/O blocks need to be retrieved from a single device. In this paper, we reevaluate the optimal cost of range queries by declustering two-dimensional datasets over multiple devices, and prove that, in general, it is impossible to achieve the new optimal cost. This is because disks cannot facilitate two-dimensional sequential access which is required by the new optimal cost. Fortunately, MEMS-based storage is being developed to reduce I/O cost. We first show that the two-dimensional sequential access requirement can not be satisfied by simply modeling MEMS-based storage as conventional disks. Then we propose a new placement scheme that exploits the physical properties of MEMS-based storage to solve this problem. Our theoretical analysis and experimental results show that the new scheme achieves almost optimal results.
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- 1.CMU CHIP project (2003), http://www.lcs.ece.cmu.edu/research/MEMS
- 2.Hewlett-packard laboratories atomic resolution storage (2003), http://www.hpl.hp.com/research/storage.html
- 3.Atallah, M.J., Prabhakar, S.: (almost) optimal parallel block access for range queries. In: Nineteenth ACM Symposium on Principles of Database Systems, PODS, May 2000, pp. 205–215 (2000)Google Scholar
- 4.Bhatia, R., Sinha, R.K., Chen, C.M.: Declustring using golden ratio sequences. In: Proc. of International Conference on Data Engineering, February 2000, pp. 271–280 (2000)Google Scholar
- 5.Faloutsos, C., Bhagwat, P.: Declustring using fractals. In: Proc. of the 2nd Int. Conf. on Parallel and Distributed Information Systems, January 1993, pp. 18–25 (1993)Google Scholar
- 6.Frikken, K., Atallah, M.J., Prabhakar, S., Safavi-Naini, R.: Optimal parallel i/o for range queries through replication. In: Proceedings of the 13th International Conference on Database and Expert Systems Applications, September 2002, pp. 669–678 (2002)Google Scholar
- 7.Griffin, J., Schlosser, S., Ganger, G., Nagle, D.: Modeling and performance of MEMS-Based storage devices. In: Proceedings of ACM SIGMETRICS, June 2000, pp. 56–65 (2000)Google Scholar
- 8.Griffin, J., Schlosser, S., Ganger, G., Nagle, D.: Operating systems management of MEMS-based storage devices. In: Symposium on Operating Systems Design and Implementation(OSDI), October 2000, pp. 227–242 (2000)Google Scholar
- 9.Yu, H., Agrawal, D., El Abbadi, A.: Tabular placement of relational data on MEMS-based storage devices. In: Proceedings of the 29th Conference on Very Large Databases(VLDB), September 2003, pp. 680–693 (2003)Google Scholar
- 10.Abdel-Ghaffar, K.A.S., El Abbadi, A.: Optimal allocation of two-dimensional data. In: International Conference on Database Theory, January 1997, pp. 408–418 (1997)Google Scholar
- 11.Prabhakar, S., Abdel-Ghaffar, K.A.S., Agrawal, D., El Abbadi, A.: Cyclic allocation of two-dimensional data. In: International Conference on Data Engineering, February 1998, pp. 94–101 (1998)Google Scholar
- 13.Schlosser, S.W., Griffin, J.L., Nagle, D.F., Ganger, G.R.: Designing computer systems with MEMS-based storage. In: Architectural Support for Programming Languages and Operating Systems, November 2000, pp. 1–12 (2000)Google Scholar