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Multimedia Tools and Applications

, Volume 78, Issue 3, pp 3435–3456 | Cite as

Version-vector based video data online cloud backup in smart campus

  • Ming TaoEmail author
  • Wenhong Wei
  • Huaqiang YuanEmail author
  • Shuqiang Huang
Article
  • 83 Downloads

Abstract

As a kind of popular multimedia service, the video business in smart campus is fully developed, and the data volume is experiencing a continuous tremendous growth. However, the video data storage also needs to cope with many security threats resulted from some uncertainly factors. Recently, data backup has been credited as an important method to address these issues. Yet, how to improve the efficiency of video data online backup remains a critical challenge. In the context of cloud computing, a version-vector based video data online backup system is proposed in this paper, which fully implements three important functions, e.g., backup, indexing and recovery. At the time of the client backuping the data to the server, the version vectors of files and data chunks are produced as metadata. Accordingly, only through exchanging a small amount of metadata between the data nodes, it can identify the redundant data such that breaking the limitations on file-level deduplication and data-chunk-level deduplication in the existing backup systems, and can further improve the performance of backup, indexing and recovery. The conducted experiments have been shown to demonstrate the efficiency.

Keywords

Video data Version-vector Cloud backup Smart campus 

Notes

Acknowledgements

This work was supported in part by the National Key R&D Program of China (Grand No. 2016YFD0400206), the National Natural Science Fund, China (Grant Nos. 61300198 & 61572131 & 61772233); the Guangdong University Scientific Innovation Project (Grant No. 2017KTSCX178); the outstanding young teacher training program of the Education Department of Guangdong Province (Grant No. YQ2015158); Guangdong Provincial Science & Technology Plan Projects (Grant No. 2016A010101035 & 2016A010101034).

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© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Computer Science and Network SecurityDongguan University of TechnologyDongguanPeople’s Republic of China
  2. 2.Department of Optoelectronic EngineeringJinan UniversityGuangzhouPeople’s Republic of China

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