Generic placeholder image

Recent Advances in Electrical & Electronic Engineering


ISSN (Print): 2352-0965
ISSN (Online): 2352-0973

Research Article

Research on the Method and Application of MapReduce in Mobile Track Big Data Mining

Author(s): Shaoyu Liang*

Volume 14, Issue 1, 2021

Published on: 20 July, 2020

Page: [20 - 28] Pages: 9

DOI: 10.2174/2352096513999200720165146

Price: $65


Background: Mass movement trajectory data with real scenarios has been evolved with big data mining to solve the data redundancy problem.

Methods: This paper proposes a parallel path based on the Map Reduce compression method, using two kinds of piecewise point mutual crisscross, the classified method of trajectory, and then segment trajectory distribution to multiple nodes to parallelize the compression.

Results: Finally, the results based on both compression methods have been simulated for the different real-time data by merging both techniques.

Conclusion: The performance test results show that the parallel trajectory compression method proposed in this paper can greatly improve the compression efficiency and completely eliminate the error caused by the failure of the correlation between the segments.

Keywords: Trajectory compression, map reduce, GPS trajectory, computing task, (k-Means) algorithm, trajectory compression algorithm.

Graphical Abstract

Rights & Permissions Print Export Cite as
© 2023 Bentham Science Publishers | Privacy Policy