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Video transcoding scheme of multimedia data-hiding for multiform resources based on intra-cloud

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Abstract

Recently, intra-cloud research has been actively conducted to reduce the waste of idle resources in distributed desktops and to increase resource utilization. Intra-cloud integrates the idle resources of distributed desktops to provide computing and storage services to users. Existing intra-cloud have only studied storage of large files and simple computing services. Research is needed for computing services of multimedia field such as video and audio in the intra-cloud. This paper proposes a diversify scheme for multiform video resources (DSMVR), which is a video transcoding scheme of multimedia data-hiding based on the parallel computing framework and the intra-cloud environment, in order to transcode for multiform resource types within the intra-cloud, which composed to computing infrastructure using legacy desktops. Its target users are community user groups within a certain size. By using a small-scale server group, parallel processing framework and improved task assignment algorithm, high-speed video transcoding can be realized by using ffmpeg, which is a vast software suite of libraries and programs designed for handling video, audio, and other multimedia files and streams, and different-definition videos are generated step by step at high speed. By using the DSMVR scheme, the size of a task can be dynamically analyzed in order to select the number of task processing servers required, thus ensuring the high scalability of the DSMVR. Thanks to these operations, the user can smoothly play videos at resolutions that are suitable for different smart devices.

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References

  • Ahmad I, Wei X, Sun Y, Zhang YQ (2005) Video transcoding: an overview of various techniques and research issues. IEEE Trans Multimed 7(5):793–804

    Article  Google Scholar 

  • Anderson TE (1990) The performance of spin lock alternatives for shared-memory multiprocessors. IEEE Trans Parallel Distrib Syst 1(1):6–16

    Article  Google Scholar 

  • Ashraf A (2013) Cost-efficient virtual machine provisioning for multi-tier web applications and video transcoding. In: Proceedings of the 13th IEEE/ACM international symposium on cluster, cloud and grid Comput, IEEE, Delft, Netherlands, 13–16 May, pp 66–69

  • Fahim Y, Rahhali H, Hanine M, Benlahmar EH, Labriji EH, Hanoune M, Eddaoui A (2018) Load balancing in cloud computing using meta-heuristic algorithm. J Inf Process Syst 14:569–587

    Google Scholar 

  • Gao G, Hu H, Wen Y, Westphal C (2017) Resource provisioning and profit maximization for transcoding in clouds: a two-timescale approach. IEEE Trans Multimed 19(4):836–848

    Article  Google Scholar 

  • Gao G, Zhang W, Wang YWZ, Zhu W, Tan YP (2014) Cost optimal video transcoding in media cloud: insights from user viewing pattern. In: Proceedings of the IEEE international conference on multimedia and expo, IEEE, Chengdu, China, 14–18 Jul, pp 1–6

  • Hsu TH, Wang ZY (2017) A distributed SHVC video transcoding system. In: Proceedings of the 10th international conference on Ubi-media computing and workshops, IEEE, Pattaya, Thailand, 1–4 Aug

  • Jokhio F, Ashraf A, Lafond S, Porres I, Lilius J (2013) Prediction-based dynamic resource allocation for video transcoding in cloud computing. In: Proceedings of 21st Euromicro international conference on parallel, distributed, and network-based processing, IEEE, Belfast, UK, 27 Feb.–1 Mar. 2013, pp 254-261

  • Kim M, Cui Y, Han S, Lee H (2013) Towards efficient design and implementation of a hadoop-based distributed video transcoding system in cloud computing environment. Int J Multimed Ubiquitous Eng 8(2):213–224

    Google Scholar 

  • Maity S, Park JH (2016) Powering IoT devices: a novel design and analysis technique. J Converg 7:1–18

    Google Scholar 

  • Mesbahi MR, Rahmani AM, Hosseinzadeh M (2018) Reliability and high availability in cloud computing environments: a reference roadmap. Hum Centric Comput Inf Sci 18(20):1–31

    Google Scholar 

  • Shanableh T, Peixoto E, Izquierdo E (2013) MPEG-2 to HEVC video transcoding with content-based modeling. IEEE Trans Circ Syst Video Technol 23(7):1191–1196

    Article  Google Scholar 

  • Son S, Kim M (2017) HVTS: Haddop-based video transcoding system for media services. IEICE Trans Fund Electron Commun Comput Sci E100-A(5):1248–1253

  • Vetro A, Christopoulos C, Sun H (2003) Video transcoding architectures and techniques: an overview. IEEE Signal Process Mag 20(2):18–29

    Article  Google Scholar 

  • Wu Y, Zhang Z, Wu C, Li Z, Lau FCM (2013) CloudMoV: Cloud-based mobile social TV. IEEE Trans Multimed 15(4):821–832

    Article  Google Scholar 

  • Zhou Y, Yu FR, Chen J, Kuo Y (2018) Video transcoding, caching, and multicast for heterogeneous networks over wireless network virtualization. IEEE Commun Lett 22(1):141–144

    Article  Google Scholar 

  • Zinner T, Hohlfeld O, Abboud O, Hossfeld T (2010) Impact of frame rate and resolution on objective QoE metrics. In: Proceedings of the second international workshop on quality of multimedia experience, IEEE, Trondheim, Norway, 21–23 Jun, pp 29–34

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Acknowledgements

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2017R1D1A1A09000631).

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Authors and Affiliations

  1. Department of Multimedia Engineering, Dongguk University, Seoul, 04620, Korea

    Hyun-Woo Kim, He Mu & Young-Sik Jeong

  2. Department of Computer Science and Engineering, Seoul National University of Science and Technology, Seoul, 01811, Korea

    Jong Hyuk Park

  3. School of Computing Science and Engineering, Vellore Institute of Technology (VIT), Vellore, 632014, India

    Arun Kumar Sangaiah

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  1. Hyun-Woo Kim
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  2. He Mu
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  3. Jong Hyuk Park
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  4. Arun Kumar Sangaiah
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  5. Young-Sik Jeong
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Correspondence to Jong Hyuk Park or Young-Sik Jeong.

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Kim, HW., Mu, H., Park, J.H. et al. Video transcoding scheme of multimedia data-hiding for multiform resources based on intra-cloud. J Ambient Intell Human Comput 11, 1809–1819 (2020). https://doi.org/10.1007/s12652-019-01279-1

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