Modelling the Value of JITEX: Just-In-Time Transcoding at the Edge

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Publisher: SMPTE — White Plains, NY, USA
Doc Type: Conference Paper
Content Type: Original Research
Volume: 2022, No. 10, pp. 1–12
Abstract: In today's CDNs, edge servers are more than just reverse proxies. Computing resources can be reserved at the edge at a lower cost thanks to adoption of virtualized technologies and the availability of datacenters deep in 5G networks. CDN administrators can then evaluate whether to run processing-intensive tasks on or near the edge servers. Through edge processing, traditional CDN management limitations can be fixed by using computing resources. Adaptive Bitrate (ABR) Over-The-Top (OTT) streaming pose a new challenge for CDN management due the plurality of assets versions. Precisely, the CDN is required to offer dozens of videos per asset in order to accommodate a broad range of client capabilities, which reduces cache performance and increases backhaul costs. A solution to this problem is to receive a pivot video and transcode it on-the-fly into different formats by the edge processing solution. In this paper, we model the impact of this solution known as just-in-time-transcoding at the edge (JITEX). To do so, an exhaustive system model is designed allowing to define diverse sets of settings, mimicking real-world streaming scenarios. The results indicates that, the use of JITEX seems to be less cost-efficient when exchanged with cache memory budget. However, when exchanged with ingress traffic budget, specially when the down-link is naturally limited, the use of JITEX appears to be more promising.
Publication Date: 2022-10-24
DOI: 10.5594/M001990
ISBN: Print: 978-1-61482-963-8
Link: https://doi.org/10.5594/M001990
Author(s): Gwendal SimonSynamedia, France
Fatemeh NasiriSynamedia, France
Jan De CockSynamedia, France
Keyword(s): Content Delivery Network, Just-in-time Transcoding, Edge Computing, Cache Management
Copyright: © 2022 Society of Motion Picture and Television Engineers, Inc.

Bibliographic Reference(s)

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Gwendal Simon, Fatemeh Nasiri, and Jan De Cock; Modelling the Value of JITEX: Just-In-Time Transcoding at the Edge, SMPTE Meetings and Conferences ( October 2022); SMPTE, 2022, ISBN: 978-1-61482-963-8. Available at https://doi.org/10.5594/M001990

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Gwendal Simon, Fatemeh Nasiri, and Jan De Cock; Modelling the Value of JITEX: Just-In-Time Transcoding at the Edge, SMPTE Meetings and Conferences ( October 2022); SMPTE, 2022, ISBN: 978-1-61482-963-8. Available at https://doi.org/10.5594/M001990

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<span class="citation">Gwendal Simon, Fatemeh Nasiri, and Jan De Cock; <cite>Modelling the Value of JITEX: Just-In-Time Transcoding at the Edge</cite>, SMPTE Meetings and Conferences ( October 2022); SMPTE, 2022, ISBN: 978-1-61482-963-8. Available at <a href="https://doi.org/10.5594/M001990" target="_blank" rel="noopener">https://doi.org/10.5594/M001990</a></span>

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Gwendal Simon, Fatemeh Nasiri, and Jan De Cock; <cite id="bib-10-5594-m001990">Modelling the Value of JITEX: Just-In-Time Transcoding at the Edge</cite>, SMPTE Meetings and Conferences ( October 2022); SMPTE, 2022, ISBN: 978-1-61482-963-8
<span class="doi">10.5594/M001990</span>
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