Indexing of Network-Constrained Moving Objects

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearch

72 Citations (Scopus)


With the proliferation of mobile computing, the ability to index efficiently the movements of mobile objects becomes important. Objects are typically seen as moving in two-dimensional (x,y) space, which means that their movements across time may be embedded in the three-dimensional (x,y,t) space. Further, the movements are typically represented as trajectories, sequences of connected line segments. In certain cases, movement is restricted, and specifically in this paper, we aim at exploiting that movements occur in transportation networks to reduce the dimensionality of the data. Briefly, the idea is to reduce movements to occur in one spatial dimension. As a consequence, the movement data becomes two-dimensional (x,t). The advantages of considering such lower-dimensional trajectories are the reduced overall size of the data and the lower-dimensional indexing challenge. Since off-the-shelf database management systems typically do not offer higher-dimensional indexing, this reduction in dimensionality allows us to use such DBM- Ses to store and index trajectories. Moreover, we argue that, given the right circumstances, indexing these dimensionality-reduced trajectories can be more efficient than using a three-dimensional index. This hypothesis is verified by an experimental study that incorporates trajectories stemming from real and synthetic road networks.
Original languageEnglish
Title of host publicationProceedings of the Eleventh International Symposium on Advances in Geographic Information Systems, New Orleans, LA November 7–8
Publication date2003
Publication statusPublished - 2003
EventIndexing of Network-Constrained Moving Objects -
Duration: 19 May 2010 → …


ConferenceIndexing of Network-Constrained Moving Objects
Period19/05/2010 → …


  • indexing moving objects
  • Spatiotemporal databases
  • moving object databases
  • indexing network data

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