On-line discovery of hot motion paths

  • Authors:
  • Dimitris Sacharidis;Kostas Patroumpas;Manolis Terrovitis;Verena Kantere;Michalis Potamias;Kyriakos Mouratidis;Timos Sellis

  • Affiliations:
  • Natl. Technical University, Athens, Greece;Natl. Technical University, Athens, Greece;Natl. Technical University, Athens, Greece;Natl. Technical University, Athens, Greece;Boston University, MA;Singapore Mgmt. Univ., Singapore;Natl. Technical University, Athens, Greece

  • Venue:
  • EDBT '08 Proceedings of the 11th international conference on Extending database technology: Advances in database technology
  • Year:
  • 2008

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Abstract

We consider an environment of numerous moving objects, equipped with location-sensing devices and capable of communicating with a central coordinator. In this setting, we investigate the problem of maintaining hot motion paths, i.e., routes frequently followed by multiple objects over the recent past. Motion paths approximate portions of objects' movement within a tolerance margin that depends on the uncertainty inherent in positional measurements. Discovery of hot motion paths is important to applications requiring classification/profiling based on monitored movement patterns, such as targeted advertising, resource allocation, etc. To achieve this goal, we delegate part of the path extraction process to objects, by assigning to them adaptive lightweight filters that dynamically suppress unnecessary location updates and, thus, help reducing the communication overhead. We demonstrate the benefits of our methods and their efficiency through extensive experiments on synthetic data sets.