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An efficient mapreduce-based parallel clustering algorithm for distributed traffic subarea division

Xia, Dawen, Wang, Binfeng, Li, Yantao, Rong, Zhuobo and Zhang, Zili 2015, An efficient mapreduce-based parallel clustering algorithm for distributed traffic subarea division, Discrete dynamics in nature and society, vol. 2015, Article Number : 793010, pp. 1-18, doi: 10.1155/2015/793010.

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Title An efficient mapreduce-based parallel clustering algorithm for distributed traffic subarea division
Author(s) Xia, Dawen
Wang, Binfeng
Li, Yantao
Rong, Zhuobo
Zhang, Zili
Journal name Discrete dynamics in nature and society
Volume number 2015
Season Article Number : 793010
Start page 1
End page 18
Total pages 18
Publisher Hindawi Publishing Corp.
Place of publication Cairo, Egypt
Publication date 2015
ISSN 1026-0226
Summary Traffic subarea division is vital for traffic system management and traffic network analysis in intelligent transportation systems (ITSs). Since existing methods may not be suitable for big traffic data processing, this paper presents a MapReduce-based Parallel Three-Phase K -Means (Par3PKM) algorithm for solving traffic subarea division problem on a widely adopted Hadoop distributed computing platform. Specifically, we first modify the distance metric and initialization strategy of K -Means and then employ a MapReduce paradigm to redesign the optimized K -Means algorithm for parallel clustering of large-scale taxi trajectories. Moreover, we propose a boundary identifying method to connect the borders of clustering results for each cluster. Finally, we divide traffic subarea of Beijing based on real-world trajectory data sets generated by 12,000 taxis in a period of one month using the proposed approach. Experimental evaluation results indicate that when compared with K -Means, Par2PK-Means, and ParCLARA, Par3PKM achieves higher efficiency, more accuracy, and better scalability and can effectively divide traffic subarea with big taxi trajectory data.
Language eng
DOI 10.1155/2015/793010
Field of Research 0102 Applied Mathematics
010204 Dynamical Systems in Applications
Socio Economic Objective 890205 Information Processing Services (incl. Data Entry and Capture)
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2015, Hindawi Publishing Corp.
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Collection: School of Information Technology
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