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DBMS techniques for lightweight computing devices

Published:12 June 2011Publication History

ABSTRACT

Lightweight computing devices are becoming ubiquitous and an increasing number of applications are being developed for these devices. Many applications deal with a significant amount of data and involve complex joins and aggregate operations which necessitate a local database management system on the device. However, scaling down the DBMS is a challenge as these devices are constrained by limited stable storage and main memory. Optimum utilization of these limited resources is a must for such a database system. New storage models that reduce storage costs are needed and the best storage scheme should be selected based on data characteristics and nature of queries. Memory should be optimally allocated among the database operators and the best query plan should be chosen depending on the amount of available memory and the underlying storage scheme.

We propose a novel storage model, ID based Storage, which reduces storage costs considerably. We present an exact algorithm for allocating memory among the database operators. Due to its high complexity, we also propose a heuristic solution based on the benefit of an operator per unit memory allocation. Our storage management and query processing strategy ensures the best storage scheme and query execution plan for a given handheld device.

References

  1. Oracle Corporation, Oracle 10 Lite, Oracle Documentation. http://www.oracle.com/technetwork/database/database-lite/documentation/database10gr3-095070.html.Google ScholarGoogle Scholar
  2. Small Databases are Beautiful, Database Trends and Applications, August 2003. http://www.dbta.com.Google ScholarGoogle Scholar
  3. Sybase Sql Anywhere. http://www.sybase.in/products/databasemanagement/sqlanywhere.Google ScholarGoogle Scholar
  4. The Simputer. http://www.simputer.org.Google ScholarGoogle Scholar
  5. A. Ammann, M. Hanrahan, and R. Krishnamurthy. Design of a Memory Resident DBMS. In IEEE COMPCON, 1985.Google ScholarGoogle Scholar
  6. C. Bobineau, L. Bouganim, P. Pucheral, and P. Valduriez. PicoDBMS: Scaling down Database Techniques for the Smartcard. In VLDB, 2000. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. L. Bouganim, P. Pucheral, and N. Anciaux. Memory Requirements for Query Execution in Highly Constrained Devices. In VLDB, 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. A. Datta, D. VanderMeer, K. Ramamritham, and B. Moon. Applying Parallel Processing Techniques in Data Warehousing and OLAP. In VLDB, 1999.Google ScholarGoogle Scholar
  9. D. J. DeWitt, R. H. Katz, F. Olken, L. D. Shapiro, M. R. Stonebraker, and D. Wood. Implementation Techniques for Main Memory Database Systems. In ACM SIGMOD, 1984. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. G. Graefe. Query evaluation techniques for large databases. In ACM Computing Survey, 1993. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. A. Hulgeri, S. Sudarshan, and S. Seshadri. Memory Cognizant Query Optimization. In COMAD, 2000.Google ScholarGoogle Scholar
  12. J. Karlsson, A. Lal, C. Leung, and T. Pham. IBM DB2 Everyplace: A Small Footprint Relational Database System. In ICDE, 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. M. Kersten, M. Franklin, G. Weikum, D. Keim, A. Buchmann, and S. Chaudhuri. A Database Striptease or How to Manage Your Personal Database. A Panel Discussion. In VLDB, 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. P. Roy. Multi-Query Optimization and Applications. PhD thesis, Indian Institute of Technology - Bombay, 2001.Google ScholarGoogle Scholar
  15. P. Selinger, M. Astrahan, D. Chamberlin, and R. Lorie. Access path selection in a relational database management system. In ACM SIGMOD, 1979. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. P. Seshadri. Honey I Shrunk the DBMS. In ACM SIGMOD, 1999. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. P. Seshadri and P. Garrett. SQL Server for Windows CE - A Database Engine for Mobile and Embedded Platforms. In ICDE, 2000.Google ScholarGoogle ScholarCross RefCross Ref

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          cover image ACM Conferences
          MobiDE '11: Proceedings of the 10th ACM International Workshop on Data Engineering for Wireless and Mobile Access
          June 2011
          50 pages
          ISBN:9781450306560
          DOI:10.1145/1999309

          Copyright © 2011 ACM

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          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 12 June 2011

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