Indexing Objects Moving on Fixed Networks

  • Elias Frentzos
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2750)


The development of a spatiotemporal access method suitable for objects moving on fixed networks is a very attractive challenge due to the great number of real-world spatiotemporal database applications and fleet management systems dealing with this type of objects. In this work, a new indexing technique, named Fixed Network R-Tree (FNR-Tree), is proposed for objects constrained to move on fixed networks in 2-dimensional space. The general idea that describes the FNR-Tree is a forest of 1-dimensional (1D) R-Trees on top of a 2-dimensional (2D) R-Tree. The 2D R-Tree is used to index the spatial data of the network (e.g. roads consisting of line segments), while the 1D R-Trees are used to index the time interval of each object’s movement inside a given link of the network. The performance study, comparing this novel access method with the traditional R-Tree under various datasets and queries, shows that the FNR-Tree outperforms the R-Tree in most cases.


Line Segment Road Network Leaf Node Range Query Query Window 
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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© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Elias Frentzos
    • 1
  1. 1.Department of Rural and Surveying EngineeringNational Technical University of AthensZographou, AthensHellas, Greece

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