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A Content-Based Publish/Subscribe Matching Algorithm for 2D Spatial Objects

  • Athanasios Konstantinidis
  • Antonio Carzaniga
  • Alexander L. Wolf
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7049)

Abstract

An important concern in the design of a publish/subscribe system is its expressiveness, which is the ability to represent various types of information in publications and to precisely select information of interest through subscriptions. We present an enhancement to existing content-based publish/subscribe systems with support for a 2D spatial data type and eight associated relational operators, including those to reveal overlap, containment, touching, and disjointedness between regions of irregular shape. We describe an algorithm for evaluating spatial relations that is founded on a new dynamic discretization method and region-intersection model. In order to make the data type practical for large-scale applications, we provide an indexing structure for accessing spatial constraints and develop a simplification method for eliminating redundant constraints. Finally, we present the results of experiments evaluating the effectiveness and scalability of our approach.

Keywords

Matching Algorithm Point Density Spatial Constraint Topological Relation Input Region 
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

© IFIP International Federation for Information Processing 2011

Authors and Affiliations

  • Athanasios Konstantinidis
    • 1
  • Antonio Carzaniga
    • 2
  • Alexander L. Wolf
    • 1
  1. 1.Department of ComputingImperial College LondonUK
  2. 2.Faculty of InformaticsUniversity of LuganoSwitzerland

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