A query processor for prediction-based monitoring of data streams

  • Authors:

  • Sergio Ilarri;Ouri Wolfson;Eduardo Mena;Arantza Illarramendi;Prasad Sistla

  • Affiliations:

  • Univ. of Zaragoza, Zaragoza, Spain;Univ. of Illinois, Chicago, IL;Univ. of Zaragoza, Zaragoza, Spain;Univ. of the Basque Country, San Sebastián, Spain;Univ. of Illinois, Chicago, IL

  • Venue:
  • Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
  • Year:
  • 2009

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Abstract

Networks of sensors are used in many different fields, from industrial applications to surveillance applications. A common feature of these applications is the necessity of a monitoring infrastructure that analyzes a large number of data streams and outputs values that satisfy certain constraints. In this paper, we present a query processor for monitoring queries in a network of sensors with prediction functions. Sensors communicate their values according to a threshold policy, and the proposed query processor leverages prediction functions to compare tuples efficiently and to generate answers even in the absence of new incoming tuples. Two types of constraints are managed by the query processor: window-join constraints and value constraints. Uncertainty issues are considered to assign probabilistic values to the results returned to the user. Moreover, we have developed an appropriate buffer management strategy, that takes into account the contributions of the prediction functions contained in the tuples. We also present some experimental results that show the benefits of the proposal.