QoE Ready to Respond: A QoE-aware MEC Selection Scheme for DASH-based Adaptive Video Streaming to Mobile Users

Wanxin Shi, Qing Li*, Ruishan Zhang, Gengbiao Shen, Yong Jiang, Zhenhui Yuan, Gabriel-Miro Muntean

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The Multi-access Edge Computing (MEC) paradigm offers cloud-computing support to rich media applications, including Dynamic Adaptive Streaming over HTTP (DASH)-based ones at the edge of the network, close to mobile users. MEC servers, typically deployed at base stations (BS), help reduce latency and improve quality of experience (QoE) of video streaming. Unfortunately the communications involving mobile users require handovers between BSs and these influence both transmission efficiency because of the relative position of the MEC servers and transit cost. At the same time, serving MEC for a mobile user should not necessarily be changed when handover occurs. This paper introduces QoE Ready to Respond (QoE-R2R), a QoE-aware MEC Selection scheme for DASH-based mobile adaptive video streaming for optimizing video transmission in a MEC-supported network environment. Simulation-based testing shows that the proposed (QoE-R2R) scheme outperforms some traditional alternative solutions. Compared to hit rate and delay-based schemes, QoE-R2R reduces by 27.6% transmission time and improves with 6.2% QoE.
Original languageEnglish
Title of host publicationMM '21
Subtitle of host publicationProceedings of the 29th ACM International Conference on Multimedia
Place of PublicationNew York
PublisherACM
Pages4016–4024
Number of pages9
ISBN (Print)9781450386517
DOIs
Publication statusPublished - 17 Oct 2021

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