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An efficient transmission method based on HEVC multi-view adaptive video streaming over P2P network in NFV

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Abstract

Researchers and entertainment companies have given lots of attention to virtual reality over the past decade. 3D multi-view is a technology that provides interactions that are similar to those in the real world. However, 3D video streaming has a high data transfer rate because we must transmit multimedia data at a rate several times higher than that used for regular streaming. Besides, network throughput is unstable due to the inherent limitations of network infrastructure, which degrades video streaming quality. Additionally, network failure can occur frequently, causing stalling in multimedia playback. Hence, a network system is required to have more than one backup route in order to successfully guarantee the reliability of a network at all times. Furthermore, in the field of multi-view transmission, not much research has been published that has been conducted in a network virtualization environment. Therefore, we present a study on adaptive-based, high-efficiency video coding with three-dimensional, multi-view streaming over a peer-to-peer network. First, we study adaptive bitrate streaming methods based on high-efficiency video coding. Then we research transmitting multi-view data over a multi-path system. In the experiment, we first record a video from different views using five cameras. Next we merge recorded videos from the five cameras into a file and encode it before transmitting it over the peer-to-peer network. Moreover, we build a virtualized system using Docker virtualization technology and network function virtualization. The results of the experiment show that transmitting high-volume data over a multi-path network channel increases the streaming buffer level, which is about 20% higher than an adaptive streaming 3D method. It also makes the video quality 4% higher than in an HEVC-based adaptive streaming method.

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Acknowledgements

This work was supported by ‘The Cross-Ministry Giga KOREA Project’ grant from the Ministry of Science, ICT and Future Planning, Republic of Korea (GK16P0100, Development of Tele Experience Service SW Platform based on Giga Media). Besides, this research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science, and Technology (MEST) (Grant No. NRF-2017R1D1A1B03034429). Furthermore, this research was supported by the Ministry of Science and ICT (MSIT), Korea, under the Information Technology Research Center (ITRC) support program (IITP-2018-2016-0-00314) supervised by the Institute for Information & communications Technology Promotion (IITP). Finally, this work was supported by Institute for Information & Communications Technology Promotion (IITP) Grant funded by the Korea government (MSIT). [2018-0-00691, Development of Autonomous Collaborative Swarm Intelligence Technologies for Disposable IoT Devices].

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Authors and Affiliations

  1. School of Electronics and Computer Engineering, Chonnam National University, 77, Yongbong-ro, Buk-gu, Gwangju, 500-757, Korea

    Linh Van Ma, Gwanghyun Yu, Jin-Young Kim, Yonggwan Won & Jinsul Kim

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  1. Linh Van Ma
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Correspondence to Jinsul Kim.

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Van Ma, L., Yu, G., Kim, JY. et al. An efficient transmission method based on HEVC multi-view adaptive video streaming over P2P network in NFV. J Supercomput 74, 6939–6959 (2018). https://doi.org/10.1007/s11227-018-2594-0

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