Cache-Enabled Adaptive Video Streaming: A QoE-Based Evaluation Study

Dynamic Adaptive Streaming over HTTP (DASH) has prevailed as the dominant way of video transmission over the Internet. This technology is based on receiving small sequential video segments from a server. However, one challenge that has not been adequately examined is the obtainment of video segments...

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Main Authors: Eirini Liotou, Dionysis Xenakis, Vasiliki Georgara, Georgios Kourouniotis, Lazaros Merakos
Format: Article
Language:English
Published: MDPI AG 2023-06-01
Series:Future Internet
Subjects:
Online Access:https://www.mdpi.com/1999-5903/15/7/221
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author Eirini Liotou
Dionysis Xenakis
Vasiliki Georgara
Georgios Kourouniotis
Lazaros Merakos
author_facet Eirini Liotou
Dionysis Xenakis
Vasiliki Georgara
Georgios Kourouniotis
Lazaros Merakos
author_sort Eirini Liotou
collection DOAJ
description Dynamic Adaptive Streaming over HTTP (DASH) has prevailed as the dominant way of video transmission over the Internet. This technology is based on receiving small sequential video segments from a server. However, one challenge that has not been adequately examined is the obtainment of video segments in a way that serves both the needs of the network and the improvement in the Quality of Experience (QoE) of the users. One effective way to achieve this is to implement and study caching and DASH technologies together. This paper investigates this issue by simulating a network with multiple video servers and a video client. It then implements both the peer-to-many communications in the context of adaptive video streaming and the video server caching algorithm based on proposed criteria that improve the status of the network and/or the user. Specifically, we investigate the scenario of delivering DASH-based content with the help of an intermediate server, apart from a main server, to demonstrate possible caching benefits for different sizes of intermediate storage servers. Extensive experimentation using emulation reveals the interplay and delicate balance between caching and DASH, guiding such network design decisions. A general tendency found is that, as the available buffer size increases, the video playback quality increases to some extent. However, at the same time, this improvement is linked to the random cache selection algorithm.
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spelling doaj.art-64f529db7c4145ad8b1c2dcfa7294ea12023-11-18T19:26:38ZengMDPI AGFuture Internet1999-59032023-06-0115722110.3390/fi15070221Cache-Enabled Adaptive Video Streaming: A QoE-Based Evaluation StudyEirini Liotou0Dionysis Xenakis1Vasiliki Georgara2Georgios Kourouniotis3Lazaros Merakos4Department of Informatics and Telecommunications, National and Kapodistrian University of Athens, 16121 Athens, GreeceDepartment of Informatics and Telecommunications, National and Kapodistrian University of Athens, 16121 Athens, GreeceDepartment of Informatics and Telecommunications, National and Kapodistrian University of Athens, 16121 Athens, GreeceDepartment of Informatics and Telecommunications, National and Kapodistrian University of Athens, 16121 Athens, GreeceDepartment of Informatics and Telecommunications, National and Kapodistrian University of Athens, 16121 Athens, GreeceDynamic Adaptive Streaming over HTTP (DASH) has prevailed as the dominant way of video transmission over the Internet. This technology is based on receiving small sequential video segments from a server. However, one challenge that has not been adequately examined is the obtainment of video segments in a way that serves both the needs of the network and the improvement in the Quality of Experience (QoE) of the users. One effective way to achieve this is to implement and study caching and DASH technologies together. This paper investigates this issue by simulating a network with multiple video servers and a video client. It then implements both the peer-to-many communications in the context of adaptive video streaming and the video server caching algorithm based on proposed criteria that improve the status of the network and/or the user. Specifically, we investigate the scenario of delivering DASH-based content with the help of an intermediate server, apart from a main server, to demonstrate possible caching benefits for different sizes of intermediate storage servers. Extensive experimentation using emulation reveals the interplay and delicate balance between caching and DASH, guiding such network design decisions. A general tendency found is that, as the available buffer size increases, the video playback quality increases to some extent. However, at the same time, this improvement is linked to the random cache selection algorithm.https://www.mdpi.com/1999-5903/15/7/221HTTP adaptive video streamingQuality of Experiencecachingvideo resolutionencodingstallings
spellingShingle Eirini Liotou
Dionysis Xenakis
Vasiliki Georgara
Georgios Kourouniotis
Lazaros Merakos
Cache-Enabled Adaptive Video Streaming: A QoE-Based Evaluation Study
Future Internet
HTTP adaptive video streaming
Quality of Experience
caching
video resolution
encoding
stallings
title Cache-Enabled Adaptive Video Streaming: A QoE-Based Evaluation Study
title_full Cache-Enabled Adaptive Video Streaming: A QoE-Based Evaluation Study
title_fullStr Cache-Enabled Adaptive Video Streaming: A QoE-Based Evaluation Study
title_full_unstemmed Cache-Enabled Adaptive Video Streaming: A QoE-Based Evaluation Study
title_short Cache-Enabled Adaptive Video Streaming: A QoE-Based Evaluation Study
title_sort cache enabled adaptive video streaming a qoe based evaluation study
topic HTTP adaptive video streaming
Quality of Experience
caching
video resolution
encoding
stallings
url https://www.mdpi.com/1999-5903/15/7/221
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AT dionysisxenakis cacheenabledadaptivevideostreamingaqoebasedevaluationstudy
AT vasilikigeorgara cacheenabledadaptivevideostreamingaqoebasedevaluationstudy
AT georgioskourouniotis cacheenabledadaptivevideostreamingaqoebasedevaluationstudy
AT lazarosmerakos cacheenabledadaptivevideostreamingaqoebasedevaluationstudy