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The VLDB Journal

, Volume 13, Issue 3, pp 240–255 | Cite as

Exploring the tradeoff between performance and data freshness in database-driven Web servers

  • Alexandros LabrinidisEmail author
  • Nick Roussopoulos
Article

Abstract.

Personalization, advertising, and the sheer volume of online data generate a staggering amount of dynamic Web content. In addition to Web caching, view materialization has been shown to accelerate the generation of dynamic Web content. View materialization is an attractive solution as it decouples the serving of access requests from the handling of updates. In the context of the Web, selecting which views to materialize must be decided online and needs to consider both performance and data freshness, which we refer to as the online view selection problem. In this paper, we define data freshness metrics, provide an adaptive algorithm for the online view selection problem that is based on user-specified data freshness requirements, and present experimental results. Furthermore, we examine alternative metrics for data freshness and extend our proposed algorithm to handle multiple users and alternative definitions of data freshness.

Keywords

Adaptive Algorithm Multiple User Alternative Definition Online Data Present Experimental Result 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin/Heidelberg 2004

Authors and Affiliations

  1. 1.Department of Computer ScienceUniversity of PittsburghPittburghUSA
  2. 2.Department of Computer ScienceUniversity of MarylandCollege ParkUSA

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