Publication Type
Conference Proceeding Article
Version
acceptedVersion
Publication Date
9-2014
Abstract
Location data becomes more and more important. In this paper, we focus on the trajectory data, and propose a new framework, namely PRESS (Paralleled Road-Network-Based Trajectory Compression), to effectively compress trajectory data under road network constraints. Different from existing work, PRESS proposes a novel representation for trajectories to separate the spatial representation of a trajectory from the temporal representation, and proposes a Hybrid Spatial Compression (HSC) algorithm and error Bounded Temporal Compression (BTC) algorithm to compress the spatial and temporal information of trajectories respectively. PRESS also supports common spatial-temporal queries without fully decompressing the data. Through an extensive experimental study on real trajectory dataset, PRESS significantly outperforms existing approaches in terms of saving storage cost of trajectory data with bounded errors.
Discipline
Computer Sciences | Databases and Information Systems | Transportation
Publication
Proceedings of the VLDB Endowment: 40th VLDB 2014, September 1-5, Hangzhou
Volume
7
First Page
661
Last Page
672
Identifier
10.14778/2732939.2732940
Publisher
VLDB Endowment
City or Country
Saratoga, CA
Citation
SONG, Renchu; SUN, Weiwei; ZHENG, Baihua; and ZHENG, Yu.
PRESS: A Novel Framework of Trajectory Compression in Road Networks. (2014). Proceedings of the VLDB Endowment: 40th VLDB 2014, September 1-5, Hangzhou. 7, 661-672.
Available at: https://ink.library.smu.edu.sg/sis_research/2504
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
http://dx.doi.org/10.14778/2732939.2732940