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2014 IEEE International Performance Computing and Communications Conference (IPCCC) (2014)
Austin, TX, USA
Dec. 5, 2014 to Dec. 7, 2014
ISBN: 978-1-4799-7575-4
pp: 1-8
Jinjun Liu , Wuhan National Laboratory for Optoelectronics, School of Computer, Huazhong University of Science and Technology, Wuhan 430074, China
Dan Feng , Wuhan National Laboratory for Optoelectronics, School of Computer, Huazhong University of Science and Technology, Wuhan 430074, China
Yu Hua , Wuhan National Laboratory for Optoelectronics, School of Computer, Huazhong University of Science and Technology, Wuhan 430074, China
Bin Peng , Wuhan National Laboratory for Optoelectronics, School of Computer, Huazhong University of Science and Technology, Wuhan 430074, China
Pengfei Zuo , Wuhan National Laboratory for Optoelectronics, School of Computer, Huazhong University of Science and Technology, Wuhan 430074, China
ABSTRACT
With the wide use of video-editing software, more and more similar videos are uploaded to the video-sharing platforms in cloud storage. The large number of near-duplicate videos would not only make the users not satisfactory, but also consume more resources with service providers. Since the near-duplicate videos have redundancy at the content level, the traditional de-duplication technology is not suitable to address the redundancies. In order to decrease the redundancy, we proposed a novel high performance provenance-based video-sharing system, called Provis. Provis records the provenance of the videos and compresses the near-duplicate videos via storing their provenance which replaces storing their video files to improve the space efficiency. When users attempt to upload the edited videos, Provis can rebuild the videos in the cloud via collecting and uploading their provenance to reduce the network overhead of uploading videos. We implemented Provis and compared its performance with other existing video compression techniques. Our evaluation shows that Provis achieves significant space savings.
INDEX TERMS
Videos, Cloud computing, Video compression, Servers, Indexes, Redundancy
CITATION

J. Liu, D. Feng, Y. Hua, B. Peng and P. Zuo, "Application-aware video-sharing services via provenance in cloud storage," 2014 IEEE International Performance Computing and Communications Conference (IPCCC), Austin, TX, USA, 2014, pp. 1-8.
doi:10.1109/PCCC.2014.7017097
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