Journal of South China University of Technology (Natural Science Edition) ›› 2018, Vol. 46 ›› Issue (12): 139-146.doi: 10.3969/j.issn.1000-565X.2018.12.017

• Traffic & Transportation Engineering • Previous Articles    

The Shortest Path Algorithm for Large-scale Traffic Network based on Cloud Computing

ZHANG Dongbo1， 2 LIN Yongjie2 LU Kai2 SHOU Yanfang3 XU Jianmin2    

  1. 1． Guangdong Institute of Intelligent Manufacturing，Key Laboratory of Modern Control Technology of Guangdong Province，Open Laboratory of Modern Control ＆ Optical，Mechanical and Electronic Technology of Guangdong Province，Guangzhou 510070， Guangdong，China; 2． School of Civil Engineering and Transportation，South China University of Technology，Guangzhou 510641，Guangdong，China;
    3． Guangzhou Institute of Modern Industrial Technology，South China University of Technology， Guangzhou 510641，Guangdong，China
  • Received:2018-01-21 Revised:2018-09-04 Online:2018-12-25 Published:2018-11-01
  • Contact: 林永杰( 1987-) ，男，博士，讲师，主要从事交通信号控制和数据挖掘研究 E-mail:linyjscut@scut.edu.cn
  • About author:张东波(1984-) ，男，博士，讲师，主要从事大数据处理和人工智能研究
  • Supported by:
    The National Natural Science Foundation of China( 61773168) and the Science and Technology Planning Project of Guangdong Province( 2016A030305001) 

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Abstract: Cloud computing usually provides dynamically scalable and virtualized computing resources through the Internet, and has widely been used in various fields, especially mass traffic processing. The MapReduce parallel programming model is a novel framework that supports the design of cloud computing algorithms, and can invoke clustered computers at different locations to conduct huge data processing. This study proposed a new computing logic on the base of MapReduce, and developed a parallel searching algorithm with subgraph partitions to search the shortest path in large-scale real traffic networks. In tests of the field networks, the proposed method can provide high-quality shortest path searching service within acceptable calculation time.

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