research-article

Optimizing the video transcoding workflow in content delivery networks

Authors:

Dilip Kumar Krishnappa,

Ramesh K. SitaramanAuthors Info & Claims

MMSys '15: Proceedings of the 6th ACM Multimedia Systems Conference

Pages 37 - 48

https://doi.org/10.1145/2713168.2713175

Published: 18 March 2015 Publication History

Abstract

The current approach to transcoding in adaptive bit rate streaming is to transcode all videos in all possible bit rates which wastes transcoding resources and storage space, since a large fraction of the transcoded video segments are never watched by users. To reduce transcoding work, we propose several online transcoding policies that transcode video segments in a "just-in-time" fashion such that a segment is transcoded only to those bit rates that are actually requested by the user. However, a reduction in the transcoding work should not come at the expense of a significant reduction in the quality of experience of the users. To establish the feasibility of online transcoding, we first show that the bit rate of the next video segment requested by a user can be predicted ahead of time with an accuracy of 99.7% using a Markov prediction model. This allows our online algorithms to complete transcoding the required segment ahead of when it is needed by the user, thus reducing the possibility of freezes in the video playback. To derive our results, we collect and analyze a large amount of request traces from one of the world's largest video CDNs consisting of over 200 thousand unique users watching 5 million videos over a period of three days. The main conclusion of our work is that online transcoding schemes can reduce transcoding resources by over 95% without a major impact on the users' quality of experience.

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Cited By

Seufert MSpangenberger MPoignée FWamser FRobitza WTimmerer CHoßfeld T(2024)COBIRAS: Offering a Continuous Bit Rate Slide to Maximize DASH Streaming Bandwidth UtilizationACM Transactions on Multimedia Computing, Communications, and Applications10.1145/367737920:10(1-24)Online publication date: 12-Jul-2024
https://dl.acm.org/doi/10.1145/3677379
Lee DKim YSong M(2023)Cost-Effective, Quality-Oriented Transcoding of Live-Streamed Video on Edge-ServersIEEE Transactions on Services Computing10.1109/TSC.2023.325642516:4(2503-2516)Online publication date: 1-Jul-2023
https://doi.org/10.1109/TSC.2023.3256425
Erfanian AAmirpour HTashtarian FTimmerer CHellwagner H(2023)CD-LwTE: Cost- and Delay-Aware Light-Weight Transcoding at the EdgeIEEE Transactions on Network and Service Management10.1109/TNSM.2022.322974420:3(3104-3118)Online publication date: Sep-2023
https://doi.org/10.1109/TNSM.2022.3229744
Show More Cited By

Index Terms

Optimizing the video transcoding workflow in content delivery networks
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision

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Published In

cover image ACM Conferences

MMSys '15: Proceedings of the 6th ACM Multimedia Systems Conference

March 2015

277 pages

ISBN:9781450333511

DOI:10.1145/2713168

General Chair:
Wei Tsang Ooi
National University of Singapore, Singapore
,
Program Chairs:
Wu-chi Feng
Portland State University
,
Feng Liu
Portland State University

Copyright © 2015 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 18 March 2015

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MMSys '15

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MMSys '15: Multimedia Systems Conference 2015

March 18 - 20, 2015

Oregon, Portland

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MMSys '15 Paper Acceptance Rate 12 of 41 submissions, 29%;

Overall Acceptance Rate 176 of 530 submissions, 33%

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Cited By

Seufert MSpangenberger MPoignée FWamser FRobitza WTimmerer CHoßfeld T(2024)COBIRAS: Offering a Continuous Bit Rate Slide to Maximize DASH Streaming Bandwidth UtilizationACM Transactions on Multimedia Computing, Communications, and Applications10.1145/367737920:10(1-24)Online publication date: 12-Jul-2024
https://dl.acm.org/doi/10.1145/3677379
Lee DKim YSong M(2023)Cost-Effective, Quality-Oriented Transcoding of Live-Streamed Video on Edge-ServersIEEE Transactions on Services Computing10.1109/TSC.2023.325642516:4(2503-2516)Online publication date: 1-Jul-2023
https://doi.org/10.1109/TSC.2023.3256425
Erfanian AAmirpour HTashtarian FTimmerer CHellwagner H(2023)CD-LwTE: Cost- and Delay-Aware Light-Weight Transcoding at the EdgeIEEE Transactions on Network and Service Management10.1109/TNSM.2022.322974420:3(3104-3118)Online publication date: Sep-2023
https://doi.org/10.1109/TNSM.2022.3229744
Lee DLee JSong M(2023)Video File Allocation for Wear-Leveling in Distributed Storage Systems With Heterogeneous Solid-State-Disks (SSDs)IEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2022.322247333:5(2477-2490)Online publication date: May-2023
https://doi.org/10.1109/TCSVT.2022.3222473
Mehmuda AMajdabadi RWang MKrishnamurthy D(2023)Antifreeze: High-Quality Adaptive Live Streaming with Real-time Transcoder2023 IEEE 48th Conference on Local Computer Networks (LCN)10.1109/LCN58197.2023.10223396(1-4)Online publication date: 2-Oct-2023
https://doi.org/10.1109/LCN58197.2023.10223396
Kim KSong M(2022)Energy-Saving SSD Cache Management for Video Servers with Heterogeneous HDDsEnergies10.3390/en1510363315:10(3633)Online publication date: 16-May-2022
https://doi.org/10.3390/en15103633
Lee DSong M(2022)Quality-Oriented Task Allocation and Scheduling in Transcoding Servers With Heterogeneous ProcessorsIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2021.307415832:3(1667-1680)Online publication date: Mar-2022
https://doi.org/10.1109/TCSVT.2021.3074158
Lee DSong M(2022)Quality-Aware Transcoding Task Allocation Under Limited Power in Live-Streaming SystemsIEEE Systems Journal10.1109/JSYST.2021.310352616:3(4368-4379)Online publication date: Sep-2022
https://doi.org/10.1109/JSYST.2021.3103526
Huang XHe LWang LLi F(2021)Towards 5G: Joint Optimization of Video Segment Caching, Transcoding and Resource Allocation for Adaptive Video Streaming in a Multi-Access Edge Computing NetworkIEEE Transactions on Vehicular Technology10.1109/TVT.2021.310815270:10(10909-10924)Online publication date: Oct-2021
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Salehi MLi XSalehi MLi X(2021)Other Aspects of Multimedia CloudsMultimedia Cloud Computing Systems10.1007/978-3-030-88451-2_8(153-162)Online publication date: 13-Sep-2021
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