Nafeh, M. orcid.org/0000-0002-6435-0216, Bozorgchenani, A. orcid.org/0000-0003-1360-6952 and Tarchi, D. orcid.org/0000-0001-7338-1957 (2022) Joint Scalable Video Coding and Transcoding Solutions for Fog-Computing-Assisted DASH Video Applications. Future Internet, 14 (9). 268. ISSN 1999-5903
Abstract
Video streaming solutions have increased their importance in the last decade, enabling video on demand (VoD) services. Among several innovative services, 5G and Beyond 5G (B5G) systems consider the possibility of providing VoD-based solutions for surveillance applications, citizen information and e-tourism applications, to name a few. Although the majority of the implemented solutions resort to a centralized cloud-based approach, the interest in edge/fog-based approaches is increasing. Fog-based VoD services result in fulfilling the stringent low-latency requirement of 5G and B5G networks. In the following, by resorting to the Dynamic Adaptive Streaming over HTTP (DASH) technique, we design a video-segment deployment algorithm for streaming services in a fog computing environment. In particular, by exploiting the inherent adaptation of the DASH approach, we embed in the system a joint transcoding and scalable video coding (SVC) approach able to deploy at run-time the video segments upon the user’s request. With this in mind, two algorithms have been developed aiming at maximizing the marginal gain with respect to a pre-defined delay threshold and enabling video quality downgrade for faster video deployment. Numerical results demonstrate that by effectively mapping the video segments, it is possible to minimize the streaming latency while maximising the users’ target video quality.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). |
Keywords: | fog computing; DASH; scalable video coding; transcoding |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 26 Jul 2023 09:21 |
Last Modified: | 26 Jul 2023 09:21 |
Published Version: | https://www.mdpi.com/1999-5903/14/9/268 |
Status: | Published |
Publisher: | MDPI AG |
Identification Number: | 10.3390/fi14090268 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:201525 |