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Cloud computing-based map-matching for transportation data center
Huang, Jian; Qie, Jinhui; Liu, Chunwei; Li, Siyang; Weng, Jingnong; Lv, Weifeng
Source PublicationElectronic Commerce Research and Applications
AbstractTransportation data center has recently become a common practice of modern integrated transportation management in major cities of China. Being the convergence center of large-scale multi-source vehicle tracking data, it caused great challenge on GPS map-matching efficiency and privacy protection. In this paper, we propose a secure parallel map-matching system based on Cloud Computing technology to meet the demand of transportation data center. The main contributions are as follows: (1) we propose a leapfrog method to improve the efficiency of traditional serial map-matching algorithm on the increasingly common high sampling rate GPS data; (2) we adapt the serial leapfrog map-matching algorithm for cloud computing environment by reforming it in the MapReduce paradigm; (3) we propose a privacy-aware map-matching model over hybrid clouds to realize the sensitive GPS data protection. We implemented the proposed map-matching system in the hadoop platform and tested its performance with a large-scale vehicle tracking dataset, which exceeds 100 billion records. The experimental results show that our approach is highly efficient and effective on massive vehicle tracking data processing. © 2015.
Indexed BySCI ; EI
Document Type期刊论文
Corresponding AuthorWeng, Jingnong
Recommended Citation
GB/T 7714
Huang, Jian,Qie, Jinhui,Liu, Chunwei,et al. Cloud computing-based map-matching for transportation data center[J]. Electronic Commerce Research and Applications,2015.
APA Huang, Jian,Qie, Jinhui,Liu, Chunwei,Li, Siyang,Weng, Jingnong,&Lv, Weifeng.(2015).Cloud computing-based map-matching for transportation data center.Electronic Commerce Research and Applications.
MLA Huang, Jian,et al."Cloud computing-based map-matching for transportation data center".Electronic Commerce Research and Applications (2015).
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