›› 2013, Vol. 28 ›› Issue (4): 597-604.doi: 10.1007/s11390-013-1360-2

Special Issue: Data Management and Data Mining

• Special Section of EDB2012 • Previous Articles     Next Articles

Online Approach for Spatio-Temporal Trajectory Data Reduction for Portable Devices

Heemin Park1, Member, IEEE, Young-Jun Lee2, Jinseok Chae2,*, Member, IEEE, and Wonik Choi3, Member, IEEE   

  1. 1. Department of Computer Software Engineering, Sangmyung University, Cheonan 330-720, Korea;
    2. Department of Computer Science and Engineering, Incheon National University, Incheon 406-772, Korea;
    3. School of Information and Communication Engineering, Inha University, Incheon 402-751, Korea
  • Received:2012-09-12 Revised:2013-05-07 Online:2013-07-05 Published:2013-07-05
  • Supported by:

    This work was supported by the Incheon National University Research Grant of Korea in 2011. The preliminary version of the paper was published in the Proceedings of EDB2012.

As location data are widely available to portable devices, trajectory tracking of moving objects has become an essential technology for most location-based services. To maintain such streaming data of location updates from mobile clients, conventional approaches such as time-based regular location updating and distance-based location updating have been used. However, these methods suffer from the large amount of data, redundant location updates, and large trajectory estimation errors due to the varying speed of moving objects. In this paper, we propose a simple but efficient online trajectory data reduction method for portable devices. To solve the problems of redundancy and large estimation errors, the proposed algorithm computes trajectory errors and finds a recent location update that should be sent to the server to satisfy the user requirements. We evaluate the proposed algorithm with real GPS trajectory data consisting of 17 201 trajectories. The intensive simulation results prove that the proposed algorithm always meets the given user requirements and exhibits a data reduction ratio of greater than 87% when the acceptable trajectory error is greater than or equal to 10 meters.

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