Nearest Neighbor Search on Moving Object Trajectories in Secondo

  • Authors:

  • Ralf Hartmut Güting;Angelika Braese;Thomas Behr;Jianqiu Xu

  • Affiliations:

  • LG Datenbanksysteme für neue Anwendungen Fakultät für Mathematik und Informatik, Fernuniversität in Hagen, Hagen, Germany D-58084;LG Datenbanksysteme für neue Anwendungen Fakultät für Mathematik und Informatik, Fernuniversität in Hagen, Hagen, Germany D-58084;LG Datenbanksysteme für neue Anwendungen Fakultät für Mathematik und Informatik, Fernuniversität in Hagen, Hagen, Germany D-58084;LG Datenbanksysteme für neue Anwendungen Fakultät für Mathematik und Informatik, Fernuniversität in Hagen, Hagen, Germany D-58084

  • Venue:
  • SSTD '09 Proceedings of the 11th International Symposium on Advances in Spatial and Temporal Databases
  • Year:
  • 2009

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Abstract

In the context of databases storing histories of movement (also called trajectories), we present two query processing operators to compute the k nearest neighbors of a moving query point within a set of moving points. Data moving points are represented as collections of point units (i.e., a time interval together with a linear movement function). The first operator, knearest , processes a stream of units arriving ordered by start time and returns the set of units representing the k nearest neighbors over time. It can be used to process a set of moving point candidates selected by other conditions. The second operator, knearestfilter , operates on a set of units indexed in an R-tree and uses some novel pruning techniques. It returns a set of candidates that can be further processed by knearest to obtain the final answer. These nearest neighbor algorithms are presented within Secondo , a complete DBMS environment for handling moving object histories. For example, candidates and final results can be visualized and animated at the user interface.