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Spatio-temporal data reduction with deterministic error bounds

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Goce TrajcevskiAuthors Info & Claims

The VLDB Journal — The International Journal on Very Large Data Bases, Volume 15, Issue 3

Pages 211 - 228

https://doi.org/10.1007/s00778-005-0163-7

Published: 01 September 2006 Publication History

Abstract

A common way of storing spatio-temporal information about mobile devices is in the form of a 3D (2D geography + time) trajectory. We argue that when cellular phones and Personal Digital Assistants become location-aware, the size of the spatio-temporal information generated may prohibit efficient processing. We propose to adopt a technique studied in computer graphics, namely line-simplification, as an approximation technique to solve this problem. Line simplification will reduce the size of the trajectories. Line simplification uses a distance function in producing the trajectory approximation. We postulate the desiderata for such a distance-function: it should be sound, namely the error of the answers to spatio-temporal queries must be bounded. We analyze several distance functions, and prove that some are sound in this sense for some types of queries, while others are not. A distance function that is sound for all common spatio-temporal query types is introduced and analyzed. Then we propose an aging mechanism which gradually shrinks the size of the trajectories as time progresses. We also propose to adopt existing linguistic constructs to manage the uncertainty introduced by the trajectory approximation. Finally, we analyze experimentally the effectiveness of line-simplification in reducing the size of a trajectories database.

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Spatio-temporal data reduction with deterministic error bounds
1. Information systems
  1. Information systems applications
2. Theory of computation
  1. Theory and algorithms for application domains
    1. Database theory

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cover image The VLDB Journal — The International Journal on Very Large Data Bases

The VLDB Journal — The International Journal on Very Large Data Bases Volume 15, Issue 3

September 2006

100 pages

ISSN:1066-8888

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Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 01 September 2006

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https://dl.acm.org/doi/10.1016/j.is.2024.102426
Li HTang BLu HCheema MJensen CIves ZBonifati AEl Abbadi A(2022)Spatial Data Quality in the IoT Era: Management and ExploitationProceedings of the 2022 International Conference on Management of Data10.1145/3514221.3522568(2474-2482)Online publication date: 10-Jun-2022
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Sun SMa SSong JYue WLin XMa T(2022)Experiments and Analyses of Anonymization Mechanisms for Trajectory Data PublishingJournal of Computer Science and Technology10.1007/s11390-022-2409-x37:5(1026-1048)Online publication date: 1-Oct-2022
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Lin XMa SJiang JHou YWo T(2021)Error Bounded Line Simplification Algorithms for Trajectory Compression: An Experimental EvaluationACM Transactions on Database Systems10.1145/347437346:3(1-44)Online publication date: 28-Sep-2021
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