Publication Type

Conference Proceeding Article

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

Research Areas

Data Management and Analytics

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

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://dx.doi.org/10.14778/2732939.2732940

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