Research and Design of Cloud Storage Platform for Field Observation Data in Alpine Area

  • Jiuyuan HuoEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11204)


With the rapid increase of field observation data volume in alpine regions, there are many problems exist in the data storage for geoscience researchers, such as lack of sufficient hardware storage devices, high maintenance costs, and incomplete storage environment. Nowadays, Cloud Storage technology which based on the open source Cloud Computing platform can effectively solve these problems. Therefore, this paper constructs and designs the field observation data Cloud storage platform in the alpine region based on the Apache Hadoop Cloud platform to realize the functions of creating, uploading and browsing of field observation data files in the Cloud Storage, so as to meet the needs of researchers to store observation data, share information and backup and so on. The system also can enable the efficient management of server resources, and provide large-scale data processing capabilities.


Cloud storage Field observation data Hadoop HDFS 



This work is supported by the CERNET Innovation Project (No. NGII20160111) and the Gansu Science and Technology Support Program (Grant number: 1606RJZA004).


  1. 1.
    Fu, B.J., Niu, D., Yu, G.R.: Ecosystem observation and research network in earth system science. Prog. Geogr. 26(1), 1–16 (2007)Google Scholar
  2. 2.
    Ding, Y.J.: China Cold and Arid Regions Environmental and Engineering Science for 50 years. Scientific Press, Beijing (2009)Google Scholar
  3. 3.
    Peng, L.: Cloud Computing. Electronic Industry Press, Beijing (2010)Google Scholar
  4. 4.
    Wu, Z.H.: Core Technology Analysis of Cloud Computing. People’s Posts and Telecommunications Press, Beijing (2011)Google Scholar
  5. 5.
    Armbrust, M., Fox, A., Griffith, R., et al.: A view of Cloud Computing. Commun. ACM 53(4), 50–58 (2010)CrossRefGoogle Scholar
  6. 6.
    Zhang, Q., Cheng, L., Boutaba, R.: Cloud Computing: state-of-the-art and research challenges. J. Internet Serv. Appl. 1(1), 7–18 (2010)CrossRefGoogle Scholar
  7. 7.
    Yang, N.: Cloud storage technology and its applications. Electron. Technol. Softw. Eng. 21, 220 (2014)Google Scholar
  8. 8.
    Palankar, M.R., Iamnitchi, A., Ripeanu, M., et al.: Amazon S3 for science grids: a viable solution? Proceedings of the 2008 International Workshop on Data-Aware Distributed Computing, pp. 55–64. ACM (2008)Google Scholar
  9. 9.
    Ghemawat, S., Gobioff, H., Leung, S.T.: The Google file system. In: Proceedings of the Nineteenth ACM Symposium on Operating Systems Principles, SOSP 2003, pp. 29–43. ACM, New York (2003)Google Scholar
  10. 10.
    Yu, Q., Ling, J.: Research of Cloud storage security technology based on HDFS. Comput. Eng. Des. 34(8), 2700–2705 (2013)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.School of Electronic and Information EngineeringLanzhou Jiaotong UniversityLanzhouPeople’s Republic of China
  2. 2.CERNET Co., Ltd.BeijingPeople’s Republic of China

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