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5G-VICTORI: Optimizing Media Streaming in Mobile Environments Using mmWave, NBMP and 5G Edge Computing

Authors: Louay Bassbouss; Mehdi Ben Fadhel; Stefan Pham; Anita Chen; Stephan Steglich; Eric Troudt; Marc Emmelmann; +7 Authors

5G-VICTORI: Optimizing Media Streaming in Mobile Environments Using mmWave, NBMP and 5G Edge Computing

Abstract

This paper describes an approach for optimizing media streaming services in mobile environments by utilizing the fifth-generation mobile network technology (5G), including millimeter Wave (mmWave) high speed data links, 5G Edge Computing and relevant state-of-the-art media streaming standards, such as Network Based Media Processing (NBMP) and Server and Network Assisted DASH (MPEG SAND). Although the solution described in this paper can be applied to media streaming in various mobility scenarios, the focus of this work is on rail environments and allowing video-on-demand (VoD) catalogues (Mediatheks) to be made available to train passengers via regular VoD apps – even when trains are not connected to the Internet. To achieve this objective, we introduce caching nodes inside trains and their respective stations. The work presented in this paper will be trialed in a railway station in Berlin, as part of the EU-funded research project, 5G-VICTORI.

Keywords

CDN, mmWave, Data Shower, SAND, NBMP, 5G; mmWave; NBMP; Edge Computing; Data Shower; SAND; CDN, Edge Computing, [INFO] Computer Science [cs], 5G

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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