SimpleTrack: adaptive trajectory compression with deterministic projection matrix for mobile sensor networks

Rana, Rajib and Yang, Mingrui and Wark, Tim and Chou, Chun Tung and Hu, Wen (2015) SimpleTrack: adaptive trajectory compression with deterministic projection matrix for mobile sensor networks. IEEE Sensors Journal, 15 (1). pp. 365-373. ISSN 1530-437X

Abstract

Some mobile sensor network applications require the sensor nodes to transfer their trajectories to a data sink. This paper proposes an adaptive trajectory (lossy) compression algorithm based on compressive sensing. The algorithm has two innovative elements. First, we propose a method to compute a deterministic projection matrix from a learnt dictionary. Second, we propose a method for the mobile nodes to adaptively predict the number of projections needed based on the speed of the mobile nodes. Extensive evaluation of the proposed algorithm using six data sets shows that our proposed algorithm can achieve submeter accuracy. In addition, our method of computing projection matrices outperforms two existing methods. Finally, comparison of our algorithm against a state-of-the-art trajectory compression algorithm shows that our algorithm can reduce the error by 10–60 cm for the same compression ratio.


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: Files associated with this item cannot be displayed due to copyright restrictions.
Faculty / Department / School: Current - Institute for Resilient Regions
Date Deposited: 07 Jun 2016 02:00
Last Modified: 02 Sep 2016 05:42
Uncontrolled Keywords: mobile sensor networks; trajectory compression; compressive sensing; adaptive compression; support vector regression; sparse coding; singular value decomposition
Fields of Research : 08 Information and Computing Sciences > 0805 Distributed Computing > 080504 Ubiquitous Computing
Identification Number or DOI: 10.1109/JSEN.2014.2335210
URI: http://eprints.usq.edu.au/id/eprint/28900

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