Processing publish/subscribe queries over distributed data streams

  • Authors:
  • Oana Jurca;Sebastian Michel;Alexandre Herrmann;Karl Aberer

  • Affiliations:
  • Ecole Polytechnique Fédérale de Lausanne, Switzerland;Ecole Polytechnique Fédérale de Lausanne, Switzerland;Ecole Polytechnique Fédérale de Lausanne, Switzerland;Ecole Polytechnique Fédérale de Lausanne, Switzerland

  • Venue:
  • Proceedings of the Third ACM International Conference on Distributed Event-Based Systems
  • Year:
  • 2009

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Abstract

We address the problem of processing continuous multi-join queries, over distributed data streams, making use of existing work in the field of publish/subscribe systems. We show how these principles can be ported to data streams, by enriching the common query model with location dependent attributes. Users can subscribe to a set of sensor attributes, a service that requires processing multi-join correlation queries. The goal is to decrease the overall network traffic consumption by removing redundant subscriptions and eliminating unrequested events close to the publishing sensors. This is non-trivial, especially in the presence of multi-join queries without any central control mechanism. Our approach is based on the concept of filter-split-forward phases for efficient subscription filtering and placement inside the network. We report on a performance evaluation using a real-world dataset, showing the suitability of our approach to reduce the overall data traffic.