Spatio-temporal compression of trajectories in road networks

Iulian Sandu Popa 1, 2 Karine Zeitouni 2 Vincent Oria 3 Ahmed Kharrat 2
1 SMIS - Secured and Mobile Information Systems
PRISM - Parallélisme, Réseaux, Systèmes, Modélisation, UVSQ - Université de Versailles Saint-Quentin-en-Yvelines, Inria Paris-Rocquencourt, CNRS - Centre National de la Recherche Scientifique : UMR8144
Abstract : With the proliferation of wireless communication devices integrating GPS technology, trajectory datasets are becomingmore and more available. The problems concerning the transmission and the storage of such data have become prominent with the continuous increase in volume of these data. A few works in the field of moving object databases deal with spatio-temporal compression. However, these works only consider the case of objects moving freely in the space. In this paper, we tackle the problem of compressing trajectory data in road networks with deterministic error bounds. We analyze the limitations of the existing methods and data models for road network trajectory compression. Then, we propose an extended data model and a network partitioning algorithm into long paths to increase the compression rates for the same error bound.We integrate these proposals with the state-of-the-art Douglas-Peucker compression algorithm to obtain a new technique to compress road network trajectory data with deterministic error bounds. The extensive experimental results confirm the appropriateness of the proposed approach that exhibits compression rates close to the ideal ones with respect to the employed Douglas-Peucker compression algorithm.
Type de document :
Article dans une revue
GeoInformatica, Springer Verlag, 2015, 19 (1), pp.117-145. 〈10.1007/s10707-014-0208-4〉
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https://hal.inria.fr/hal-01096623
Contributeur : Luc Bouganim <>
Soumis le : mercredi 17 décembre 2014 - 17:59:54
Dernière modification le : jeudi 11 janvier 2018 - 06:21:31

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Iulian Sandu Popa, Karine Zeitouni, Vincent Oria, Ahmed Kharrat. Spatio-temporal compression of trajectories in road networks. GeoInformatica, Springer Verlag, 2015, 19 (1), pp.117-145. 〈10.1007/s10707-014-0208-4〉. 〈hal-01096623〉

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