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Research on Hybrid Storage Method of Massive Heterogeneous Data for Mobile Environment

  • Shanshan Wu
  • Fan Yi
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 474)

Abstract

The article relates to a hybrid storage system and method for processing massive heterogeneous data, mainly for the real-time information collection, high-speed storage and timely indexing in the mobile environment. The article provides a common heterogeneous data resource metadata description model, data mixed storage solution to standardize the sharing process of massive heterogeneous data resources, and provides an optimized index construction algorithm and data archiving method to realize the collection of massive data, index building and persistence, in order to complete the data resources sharing and effective use in mobile environment. The method in the article can effectively deal with various complex problems in mobile environment, for example, the heterogeneous data structure, a huge number, scattered physical location, the data complex content and so on.

Keywords

Hybrid storage Massive heterogeneous data Real-time information collection Timely indexing Mobile environment 

References

  1. 1.
    Huang, Y.H., Li, G.Y.: Descriptive models for Internet of Things. In: International Conference on Intelligent Control and Information Processing, Harbin, China, pp. 483–486. IEEE Press (2010)Google Scholar
  2. 2.
    Xu, L.D., He, W., Li, S.: Internet of Things in industries: a survey. IEEE Trans. Ind. Inf. 10(4), 2233–2243 (2014)CrossRefGoogle Scholar
  3. 3.
    Yuxiang, Y., Cheng, X.: A development analysis of China’s intelligent transportation system. In: Proceedings of the 2012 IEEE 16th International Conference on Computer Supported Cooperative Work in Design (CSCWD), 23–25 May 2012 Google Scholar
  4. 4.
    Wang, H., Zhang, T., Quan, Y., et al.: Research on the framework of the environment Internet of Things. Int. J. Sustain. Dev. Work Ecol. 20(3), 199–204 (2013)CrossRefGoogle Scholar
  5. 5.
    Duan, Y.-E.: Design of intelligent agriculture management information system based on IoT. In: Proceedings of the 2011 International Conference on Intelligent Computation Technology and Automation (ICICTA), 28–29 March 2011Google Scholar
  6. 6.
    Lu, D., Liu, T.: The application of IOT in medical system. In: International Symposium on IT in Medicine and Education, pp. 272–275. IEEE (2011)Google Scholar
  7. 7.
    Datta, S.K., Rui, P.F.D.C., Bonnet, C., et al.: oneM2M architecture based IoT framework for mobile crowd sensing in smart cities. In: European Conference on Networks and Communications (2016)Google Scholar
  8. 8.
    Jian, A., Xiaolin, G., Jianwei, Y., et al.: Mobile crowd sensing for Internet of Things: a credible crowdsourcing model in mobile-sense service. In: IEEE International Conference on Multimedia Big Data, pp. 92–99. IEEE (2015)Google Scholar
  9. 9.
    Jeffery, K.G.: The Internet of Things: the death of traditional database? IEEE Techn. Rev. 26, 311–312 (2009)CrossRefGoogle Scholar
  10. 10.
    James, A., Cooper, J., Jeffery, K.: Research Directions in Database Architectures for the Internet of Things: A Communication of the First International Workshop on Database Architectures for the Internet of Things (DAIT 2009) (2009)Google Scholar
  11. 11.
    Zhang, Y., Han, W., Wang, W., et al.: Optimizing the storage of massive electronic pedigrees in HDFS. In: Proceedings of the 3rd International Conference on the Internet of Things, pp. 68–75. IEEE (2012)Google Scholar
  12. 12.
    Zhang, G., Li, C., Zhang, Y., et al.: SemanMedical: a kind of semantic medical monitoring system model based on the IoT sensors. In: Proceedings of the IEEE 14th International Conference on e-Health Networking, Applications and Services, pp. 238–243. IEEE (2012)Google Scholar
  13. 13.
    Paul, L., Dirk, M., Andre, B.: HashFS: applying hashing to optimize file systems for small file reads. In: Proceedings of the International Workshop on Storage Network Architecture and Parallel I/Os, pp. 33–42. IEEE (2010)Google Scholar
  14. 14.
    Zhang, Y., Liu, D.: Improving the efficiency of storing for small files in HDFS. In: Proceedings of the International Conference on Computer Science and Service System, pp. 2239–2242. IEEE (2012)Google Scholar
  15. 15.
    Yang, H., Qin, Y., Feng, G., et al.: Online monitoring of geological CO2 storage and leakage based on wireless sensor networks. IEEE Sens. J. 13(2), 556–562 (2013)CrossRefGoogle Scholar
  16. 16.
    Chang, P., Wand, T.: Supporting personal mobility with integrated RFID in VoIP systems. In: Proceedings of the International Conference on New Trends in Information and Service, pp. 1352–1359. IEEE (2009) Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Science and Technology on Information Systems Engineering LaboratoryNanjing Research Institute of Electronics EngineeringNanjingChina
  2. 2.School of SoftwareXiDian UniversityXi’anChina

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