A Novel Strategy to Achieve Video Transcoding Using Cloud Computing
One of the fundamental challenges faced in deploying multimedia systems is delivering smooth and uninterrupted audio-visual information anywhere and anytime. In such systems, multimedia content is compressed within a certain format, this requires format conversion for various devices. Thus, a transcoding mechanism is required to make the content adaptive for various devices in the network. Video transcoding converts one digitally encoded format into another, this involves translating any file format containing video and audio at the same time. This is an essential feature for devices that do not support a specific format of media or have limited storage that requires a reduced file size. Through this paper, we provide a novel way of transcoding the block-based video coding schemes using cloud architecture by establishing a video pipelining architecture. The solution discussed in this paper would enable the end users to extract videos in any format and resolution seamlessly, combined with the scalability, reliability, and cost-effectiveness of the cloud. The proposed idea would be lucrative for all the video streaming applications that are currently relying on their legacy infrastructure for video transcoding.
This work is licensed under a Creative Commons Attribution 4.0 International License.
- Ahmad, I., Wei, X., Sun, Y., and Zhang, Y.-Q. 2005. Video transcoding: An overview of various techniques and research issues. Trans. Multi. 7, 5 (oct), 793–804. DOI: https://doi.org/10.1109/TMM.2005.854472
- Garcia, A., Kalva, H., and Furht, B. 2010. A study of transcoding on cloud environments for video content delivery. MCMC ’10. Association for Computing Machinery, New York, NY, USA, 13–18. DOI: https://doi.org/10.1145/1877953.1877959
- Li, X., Salehi, M. A., and Bayoumi, M. 2016. High performance on-demand video transcoding using cloud services. CCGRID ’16. IEEE Press, 600–603. DOI: https://doi.org/10.1109/CCGrid.2016.50
- Gupta, A. and Prabhat, P., 2022. Towards a resource efficient and privacy-preserving framework for campus-wide video analytics-based applications. Complex & Intelligent Systems, pp.1-16. DOI: https://doi.org/10.1007/s40747-022-00783-w
- Sahoo, S., Sahoo, B., and Turuk, A. 2018. Video Transcoding Services in Cloud Computing Environment. 417–433. DOI: https://doi.org/10.1007/978-3-319-73676-1_16
- Shen, B., Tan, W.-T., and Huve, F. 2008. Dynamic video transcoding in mobile environments. Multimedia, IEEE 15, 42–51. International Journal of Next-Generation Computing - Special Issue, Vol. 13, No. 2, April 2022. DOI: https://doi.org/10.1109/MMUL.2008.5