Advertisement

Incremental Query Answering Using a Multi-layered Database Model in a Mobile Computing Environment

  • Sanjay Kumar Madria
  • Yongjian Fu
  • Sourav Bhowmick
Conference paper
  • 495 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2736)

Abstract

In this paper, we present incremental and intelligent query answering techniques using a multi-layered database (MLDB) in a mobile environment. We discuss static and dynamic ways of generating MLDB and explore the issues of join and updates in maintaining MLDB. We explore various issues in answering queries incrementally and intelligently.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [HFN]
    Han, J., Fu, Y., Ng, R.: Cooperative Query Answering Using Multiple Layered Databases. In: Second International Conference on Cooperative Information System(COOPIS 1994), Toronto, Canada, pp. 47–58 (May 1994)Google Scholar
  2. [HHCF]
    Han, J., Huang, Y., Cercone, N., Fu, Y.: Intelligent Query Answering by Knowledge Discovery Techniques. IEEE Transactions on Knowledge and Data Engineering 8(3), 373–390 (1996)CrossRefGoogle Scholar
  3. [MMR]
    Madria, S.K., Mohania, M., Roddick, J.: Query Processing in Mobile Databases Using Concept Hierarchy and Summary Database. In: Proc. of 5th International Conference on Foundation for Data Organization (FODO 1998), Kobe, Japan (November 1998)Google Scholar
  4. [MBMB]
    Madria, S.K., Bhargava, B., Mohania, M., Bhowmick, S.S.: Data and Transaction Management in a Mobile Environment. To appear as a book chapter in Mobile Computing: Implementing Pervasive Information and Communication Technologies. Kluwer Academic Publishers, Dordrecht (2002)Google Scholar
  5. [RFS]
    Read, R.L., Fussell, D.S., Silberschatz, A.: A Multi-Resolution Relational Data Model. In: VLDB, pp. 139–150 (1992)Google Scholar
  6. [SY]
    Singhal, M., Yang, Y.: Fast Join Execution Using Summary Information in Large Databases, Technical Report, Ohio State University (Also in CAMM NSF workshop, Brown University, 2002) (1997)Google Scholar
  7. [V]
    Vrbsky, S.V.: A Data Model for Approximate Query Processing of Real-time Database. Data & Knowledge Engineering 21, 79–102 (1997)CrossRefGoogle Scholar
  8. [VL]
    Vrbsky, S.V., Liu, J.: APPROXIMATE: A Query Processor that Produces Monotonically Improving Approximate Answers. IEEE Trans. On Knowledge and Data Engineering 5(6), 1056–1058 (1993)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Sanjay Kumar Madria
    • 1
  • Yongjian Fu
    • 1
  • Sourav Bhowmick
    • 2
  1. 1.Department of Computer ScienceUniversity of Missouri-RollaRollaUSA
  2. 2.School of Computer EngineeringNanyang Technological UniversitySingapore

Personalised recommendations