research-article

Improving Video Quality in Crowded Networks Using a DANE

Authors:

Jan Willem Kleinrouweler,

Britta Meixner,

Pablo CesarAuthors Info & Claims

NOSSDAV'17: Proceedings of the 27th Workshop on Network and Operating Systems Support for Digital Audio and Video

Pages 73 - 78

https://doi.org/10.1145/3083165.3083167

Published: 20 June 2017 Publication History

Abstract

Dynamic Adaptive Streaming over HTTP (DASH) is a technology for delivering video content over the Internet. It provides an effective mechanism, which has been adopted by major content providers. Nevertheless, available DASH player implementations have a number of drawbacks such as performance problems on shared network connections, which lead to video freezes and frequent video quality changes. In this paper, we propose a method to reduce the performance problems that exist in networks with a large number of DASH players. These networks can be found in hotels, apartment complexes, and airports. In experiments with up to 600 simultaneously active players, we are able to reduce the number of DASH players with freezes by 95% (from 345 to 15) compared to throughput-based adaptation and by 75% (from 62 to 15) compared to BOLA using our DASH Assisting Network Element (DANE). In addition, we reduced the number of quality switches by 94% compared to throughput-based adaptation, and by 85% compared to BOLA.

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Cited By

Belda RArce PGuerri Jde Fez I(2023)A DASH server-side delay-based representation switching solution to improve the quality of experience for low-latency live video streamingComputer Networks: The International Journal of Computer and Telecommunications Networking10.1016/j.comnet.2023.109961235:COnline publication date: 1-Nov-2023
https://dl.acm.org/doi/10.1016/j.comnet.2023.109961
Latif AParameswaran RVishwarupe SKhreishah AJararweh YAlenezi A(2022)MediaFlow: Multicast Routing and In-Network Monitoring for Professional Media ProductionIEEE Transactions on Network and Service Management10.1109/TNSM.2022.315516919:2(1862-1875)Online publication date: Jun-2022
https://doi.org/10.1109/TNSM.2022.3155169
Sani YQuinlan JSreenan C(2022)A bio-inspired managed video delivery service using HTTP-based adaptive streamingMultimedia Systems10.1007/s00530-022-00894-x28:3(1083-1097)Online publication date: 14-Feb-2022
https://doi.org/10.1007/s00530-022-00894-x
Show More Cited By

Index Terms

Improving Video Quality in Crowded Networks Using a DANE
1. Information systems
  1. Information systems applications
    1. Multimedia information systems
      1. Multimedia streaming
2. Networks
  1. Network services
    1. Network management

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cover image ACM Conferences

NOSSDAV'17: Proceedings of the 27th Workshop on Network and Operating Systems Support for Digital Audio and Video

June 2017

105 pages

ISBN:9781450350037

DOI:10.1145/3083165

Copyright © 2017 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 the author(s) 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: 20 June 2017

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MMSys'17

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MMSys'17: Multimedia Systems Conference 2017

June 20 - 23, 2017

Taipei, Taiwan

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NOSSDAV'17 Paper Acceptance Rate 15 of 40 submissions, 38%;

Overall Acceptance Rate 118 of 363 submissions, 33%

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Cited By

Belda RArce PGuerri Jde Fez I(2023)A DASH server-side delay-based representation switching solution to improve the quality of experience for low-latency live video streamingComputer Networks: The International Journal of Computer and Telecommunications Networking10.1016/j.comnet.2023.109961235:COnline publication date: 1-Nov-2023
https://dl.acm.org/doi/10.1016/j.comnet.2023.109961
Latif AParameswaran RVishwarupe SKhreishah AJararweh YAlenezi A(2022)MediaFlow: Multicast Routing and In-Network Monitoring for Professional Media ProductionIEEE Transactions on Network and Service Management10.1109/TNSM.2022.315516919:2(1862-1875)Online publication date: Jun-2022
https://doi.org/10.1109/TNSM.2022.3155169
Sani YQuinlan JSreenan C(2022)A bio-inspired managed video delivery service using HTTP-based adaptive streamingMultimedia Systems10.1007/s00530-022-00894-x28:3(1083-1097)Online publication date: 14-Feb-2022
https://doi.org/10.1007/s00530-022-00894-x
Begen AFeamster NLutu A(2021)Manus manum lavatProceedings of the 2021 Applied Networking Research Workshop10.1145/3472305.3472886(82-84)Online publication date: 24-Jul-2021
https://dl.acm.org/doi/10.1145/3472305.3472886
Bayhan SMaghsudi SZubow A(2021)EdgeDASH: Exploiting Network-Assisted Adaptive Video Streaming for Edge CachingIEEE Transactions on Network and Service Management10.1109/TNSM.2020.303714718:2(1732-1745)Online publication date: Jun-2021
https://doi.org/10.1109/TNSM.2020.3037147
Abar TBen Letaifa AEl Asmi S(2021)User behavior-ensemble learning based improving QoE fairness in HTTP adaptive streaming over SDN approach10.1016/bs.adcom.2021.01.004(245-269)Online publication date: 2021
https://doi.org/10.1016/bs.adcom.2021.01.004
Belmoukadam OJawad Khokhar MBarakat C(2021)On accounting for screen resolution in adaptive video streamingInternational Journal of Network Management10.1002/nem.212831:1Online publication date: 7-Jan-2021
https://dl.acm.org/doi/10.1002/nem.2128
Pham SHeeren PSchmidt CSilhavy DArbanowski S(2020)Evaluation of Shared Resource Allocation Using SAND for ABR StreamingACM Transactions on Multimedia Computing, Communications, and Applications10.1145/338892616:2s(1-18)Online publication date: 10-Jul-2020
https://dl.acm.org/doi/10.1145/3388926
Catalan-Cid MCamps-Mur DMontagud MBetzler ACivanlar MSassatelli LLee J(2020)FALCONProceedings of the 30th ACM Workshop on Network and Operating Systems Support for Digital Audio and Video10.1145/3386290.3396931(14-20)Online publication date: 10-Jun-2020
https://dl.acm.org/doi/10.1145/3386290.3396931
De Cicco LManfredi GMascolo SPalmisano VAlameda-Pineda, DRedi DCelis PSebe PChang P(2019)QoE-fair Resource Allocation for DASH Video Delivery SystemsProceedings of the 1st International Workshop on Fairness, Accountability, and Transparency in MultiMedia10.1145/3347447.3356753(33-39)Online publication date: 15-Oct-2019
https://dl.acm.org/doi/10.1145/3347447.3356753
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