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:: Volume 6, Issue 3 (12-2018) ::
jgit 2018, 6(3): 15-30 Back to browse issues page
Data Reduction of Spatio-temporal Trajectories using a Modified Online Compression Algorithm
Afsaneh Nasiri, Sanaz Azimi, Rahim Ali Abbaspour *
University of Tehran
Abstract:   (2665 Views)
With development of mobile devices equipped with a global positioning system, such as smartphones, large amounts of spatial information are generated. These data, which are often stored and modeled as a sequence of spatial locations over time, are called trajectory. The large amount of trajectory data has increased the cost of transferring, storing and processing such data. To overcome these problems, a number of compression algorithms have been proposed for reducing the size of trajectory data. In this paper, seven algorithms including uniform sampling, Douglas Poker, TD-TR, Opening Window, OPW-TR, TD-SB and SQUISH-E algorithms are being discussed and the advantages and disadvantages of these algorithms are investigated as well. The SQUISH-E algorithm can create a balance between the compression rate and the Synchronized Euclidean Distance error, but has a high compression rate than other compression algorithms. To solve mentioned problem, this paper proposed a method for changing the priority window of the SQUISH-E algorithm, which improves the compression rate of this algorithm. In order to evaluate the performance of the proposed method, all algorithms are implemented on six trajectories of varying complexity and compared with each other in terms of criteria such as compression rate, run-time, and concurrency Euclidean distance errors. The results of implementation of the proposed method indicate the improvement of the proposed algorithm at the compression rate, computation time, and Synchronized Euclidean Distance error. In compare to SQUISH-E algorithm, the computation time and compression rate of proposed algorithm is decreased about 130 millisecond and 0.015, respectively.
Keywords: Spatio-temporal Trajectories, Compression, SQUISH-E Algorithm, Priority Window.
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Type of Study: Research | Subject: GIS
Received: 2018/12/25 | Accepted: 2018/12/25 | Published: 2018/12/25
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Nasiri A, Azimi S, Abbaspour R A. Data Reduction of Spatio-temporal Trajectories using a Modified Online Compression Algorithm. jgit 2018; 6 (3) :15-30
URL: http://jgit.kntu.ac.ir/article-1-615-en.html

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Volume 6, Issue 3 (12-2018) Back to browse issues page
نشریه علمی-پژوهشی مهندسی فناوری اطلاعات مکانی Engineering Journal of Geospatial Information Technology
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