Cloud media video encoding: review and challenges

Abstract

In recent years, Internet traffic patterns have been changing. Most of the traffic demand by end users is multimedia, in particular, video streaming accounts for over 53%. This demand has led to improved network infrastructures and computing architectures to meet the challenges of delivering these multimedia services while maintaining an adequate quality of experience. Focusing on the preparation and adequacy of multimedia content for broadcasting, Cloud and Edge Computing infrastructures have been and will be crucial to offer high and ultra-high definition multimedia content in live, real-time, or video-on-demand scenarios. For these reasons, this review paper presents a detailed study of research papers related to encoding and transcoding techniques in cloud computing environments. It begins by discussing the evolution of streaming and the importance of the encoding process, with a focus on the latest streaming methods and codecs. Then, it examines the role of cloud systems in multimedia environments and provides details on the cloud infrastructure for media scenarios. After doing a systematic literature review, we have been able to find 49 valid papers that meet the requirements specified in the research questions. Each paper has been analyzed and classified according to several criteria, besides to inspect their relevance. To conclude this review, we have identified and elaborated on several challenges and open research issues associated with the development of video codecs optimized for diverse factors within both cloud and edge architectures. Additionally, we have discussed emerging challenges in designing new cloud/edge architectures aimed at more efficient delivery of media traffic. This involves investigating ways to improve the overall performance, reliability, and resource utilization of architectures that support the transmission of multimedia content over both cloud and edge computing environments ensuring a good quality of experience for the final user.

Publication DOI: https://doi.org/10.1007/s11042-024-18763-2
Divisions: College of Engineering & Physical Sciences
College of Engineering & Physical Sciences > School of Computer Science and Digital Technologies
Aston University (General)
Funding Information: Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. Grant by PID2021-126209OB-I00 funded by MCIN/AEI/10.13039/501100011033 and by “ERDF A way of making Europe”, by the “European Union” The research stay abroad of the autho
Additional Information: Copyright © The Author(s) 2024. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit https://creativecommons.org/licenses/by/4.0/
Uncontrolled Keywords: cloud comnputing,multimedia,coding,encoding,transcoding,review,survey
Publication ISSN: 1573-7721
Last Modified: 18 Apr 2025 07:25
Date Deposited: 11 Apr 2025 15:25
Full Text Link:
Related URLs: https://link.sp ... 042-024-18763-2 (Publisher URL)
PURE Output Type: Article
Published Date: 2024-10
Published Online Date: 2024-03-09
Accepted Date: 2024-02-24
Authors: Moina-Rivera, Wilmer
Garcia-Pineda, Miguel
Gutiérrez-Aguado, Juan
Alcaraz-Calero, Jose M. (ORCID Profile 0000-0002-2654-7595)

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