A Platform for Massive Railway Information Data Storage

Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 260)

Abstract

With the development of national large-scale railway construction, massive railway information data emerge rapidly, and then how to store and manage these data effectively becomes very significant. This paper puts forward a method based on distributed computing technology to store and manage massive railway information data, builds massive railway information data storage platform by using the Linux cluster technology. This system consists of three levels including data access layer, data management layer, application interface layer, enjoying safety and reliability, low operation cost, fast processing speed, easy expansibility characteristics, which shall satisfy the massive railway information data storage requirement.

Keywords

Massive railway information data storage Hadoop distributed technology Cluster system 

Notes

Acknowledgments

This research is supported by National Natural Science Foundation of China under Grant 61071076, the National High-tech Research And Development Plans (863Program) under Grant 2011AA010104-2, the Beijing Municipal Natural Science Foundation under Grant 4132057.

References

  1. 1.
    Dean J, Ghemawat S (2008) MapReduce: simplified data processing on large clusters. Commun ACM 51(01):107–113CrossRefGoogle Scholar
  2. 2.
  3. 3.
    Papadimitriou S, Sun J (2008) DisCo: distributed co-clustering with Map-Reduce. IEEE ICDM’08, 2008, pp 512–521Google Scholar
  4. 4.
    Yang HC, Dasdan A, Hsiao RL, Parker DS (2007) Mapreduce-merge: simplified relational data processing on large clusters. SCMD’07, 2007, pp 1029–1040Google Scholar
  5. 5.
    Li Y (2010) Research on parallelization of clustering algorithm based on MapReduce. Zhongshan University 2010, pp 30–33Google Scholar
  6. 6.
    Xue-song D, Jing Z, Qiang G (2010) A massive data management system based on the hadoop. Microcomput Inf 26(05-I):202–204Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  1. 1.School of Electronic and Information EngineeringBeijing Jiaotong UniversityBeijingChina
  2. 2.Key Laboratory of Communication and Information Systems, Beijing Municipal Commission of EducationBeijing Jiaotong UniversityBeijingChina
  3. 3.China Information Technology Security Evaluation CenterBeijingChina

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