SCINTRA: A Model for Quantifying Inconsistencies in Grid-Organized Sensor Database Systems

  • Lutz Schlesinger
  • Wolfgang Lehner
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2790)


Sensor data sets are usually collected in a centralized sensor database system or replicated cached in a distributed system to speed up query evaluation. However, a high data refresh rate disallows the usage of traditional replicated approaches with its strong consistency property. Instead we propose a combination of grid computing technology with sensor database systems. Each node holds cached data of other grid members. Since cached information may become stale fast, the access to outdated data may sometimes be acceptable if the user has knowledge about the degree of inconsistency if unsynchronized data are combined. The contribution of this paper is the presentation and discussion of a model for describing inconsistencies in grid organized sensor database systems.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [AdLi80]
    Adiba, M.E., Lindsay, B.G.: Database Snapshots. In: Proceedings of the 6th International Conference on Very Large Data Bases (VLDB 1980), Montreal, Canada, October 1–3, pp. 86–91 (1980)Google Scholar
  2. [BoGS01]
    Bonnet, P., Gehrke, J., Seshadri, P.: Towards Sensor Database Systems. In: Tan, K.-L., Franklin, M.J., Lui, J.C.-S. (eds.) MDM 2001. LNCS, vol. 1987, pp. 3–14. Springer, Heidelberg (2000)CrossRefGoogle Scholar
  3. [FoKe99]
    Foster, T., Kesselman, C. (Hrsg.): The Grid: Blueprint for a New Computing Infrastructure. Morgan Kaufmann Verlag, San Francisco (1999)Google Scholar
  4. [IBM01]
    N.N.: The Garlic Project, IBM Corp. (2001)Google Scholar
  5. [Inmo96]
    Inmon, W.H.: Building the Data Warehouse, 2nd edn. John Wiley & Sons, Inc., New York (1996)Google Scholar
  6. [ÖzVa91]
    Özsu, M., Valduriez, P.: Principles of Distributed Database Systems. Prentice-Hall, Englewood Cliffs (1991)Google Scholar
  7. [RoSc97]
    Roth, M.T., Schwarz, P.M.: Don’t Scrap It, Wrap It! A Wrapper Architecture for Legacy Data Sources. In: Proceedings of 23rd International Conference on Very Large Data Bases (VLDB 1997), Athens, Greece, August 25–29, pp. 266–275 (1997)Google Scholar
  8. [ScLe02]
    Schlesinger, L., Lehner, W.: Extending Data Warehouses by Semi- Consistent Database Views. In: Proceedings of the 4th International Workshop on Design and Management of Data Warehouses (DMDW 2002), Toronto, Canada, May 27 (2002)Google Scholar
  9. [SeLR95]
    Seshadri, P., Livny, M., Ramakrishnan, R.: SEQ: A Model for Sequence Databases. In: Proceedings of the 11th International Conference on Data Engineering (ICDE), Taipei, Taiwan, March 6–10, pp. 232–239 (1995)Google Scholar
  10. [TCG+93]
    Tansel, A., Clifford, J., Gadia, S., Jajodia, S., Segev, A., Snodgrass, R.: Temporal Databases. Benjamin/Cummings Publishing, Redwood City (1993)Google Scholar
  11. [Wied92]
    Wiederhold, G.: Mediators in the architecture of future information systems. IEEE Computer 25(3), 38–49 (1992)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Lutz Schlesinger
    • 1
  • Wolfgang Lehner
    • 2
  1. 1.Department of Database SystemsUniversity of Erlangen-NurembergErlangenGermany
  2. 2.Dresden University of Technology Database Technology GroupDresdenGermany

Personalised recommendations