Approximate Continuous Query Answering over Streams and Dynamic Linked Data Sets

  • Soheila Dehghanzadeh
  • Daniele Dell’Aglio
  • Shen Gao
  • Emanuele Della Valle
  • Alessandra  Mileo
  • Abraham Bernstein
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9114)

Abstract

To perform complex tasks, RDF Stream Processing Web applications evaluate continuous queries over streams and quasi-static (background) data. While the former are pushed in the application, the latter are continuously retrieved from the sources. As soon as the background data increase the volume and become distributed over the Web, the cost to retrieve them increases and applications become unresponsive. In this paper, we address the problem of optimizing the evaluation of these queries by leveraging local views on background data. Local views enhance performance, but require maintenance processes, because changes in the background data sources are not automatically reflected in the application. We propose a two-step query-driven maintenance process to maintain the local view: it exploits information from the query (e.g., the sliding window definition and the current window content) to maintain the local view based on user-defined Quality of Service constraints. Experimental evaluation show the effectiveness of the approach.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Soheila Dehghanzadeh
    • 1
  • Daniele Dell’Aglio
    • 2
  • Shen Gao
    • 3
  • Emanuele Della Valle
    • 2
  • Alessandra  Mileo
    • 1
  • Abraham Bernstein
    • 3
  1. 1.INSIGHT Research CenterNUI GalwayGalwayIreland
  2. 2.DEIBPolitecnico of MilanoMilanItaly
  3. 3.Department of InformaticsUniversity of ZurichZurichSwitzerland

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