research-article

MASERATI: mobile adaptive streaming based on environmental and contextual information

Authors:

Myungchul Kwak,

Ted Taekyoung Kwon,

Yanghee ChoiAuthors Info & Claims

WiNTECH '13: Proceedings of the 8th ACM international workshop on Wireless network testbeds, experimental evaluation & characterization

Pages 33 - 40

https://doi.org/10.1145/2505469.2505473

Published: 30 September 2013 Publication History

Abstract

Wireless/mobile video streaming has become increasingly popular, which makes wireless link bandwidth scarce. To provide streaming services to mobile users, it is crucial to adapt to the link condition and traffic fluctuation. We investigate which factors in natural environments and user contexts affect the available link bandwidth. To this end, we conduct a measurement study which contains 38 repeated trips along the same 5~km circular road in the campus of Seoul National University in April and May 2013. We measure the download throughput of video streaming from two different networks (3G and 4G LTE) with varying location, time, humidity, and speed. Our measurement results reveal that the humidity and location are the more important factors in the 3G network, while the speed, time, and location are the more important ones in the 4G LTE network to predict the available link bandwidth. We then propose an adaptive video streaming framework, MASERATI, where the information of environments and contexts is used to predict the available bandwidth. We demonstrate that MASERATI significantly improves the QoE of mobile streaming users in terms of the playout success rate, video quality, and stability, in comparison to DASH.

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Cited By

Elsherbiny HNagib AAbou-zeid HAbbas HHassanein HNoureldin ABin Sediq ABoudreau G(2020)4G LTE Network Data Collection and Analysis along Public Transportation RoutesGLOBECOM 2020 - 2020 IEEE Global Communications Conference10.1109/GLOBECOM42002.2020.9348031(1-6)Online publication date: Dec-2020
https://doi.org/10.1109/GLOBECOM42002.2020.9348031
Cho SKim DKim CJeong KSohn C(2019)360-Degree Video Traffic Reduction Using Cloud Streaming in MobileWireless Personal Communications: An International Journal10.1007/s11277-018-5984-y105:2(635-654)Online publication date: 1-Mar-2019
https://dl.acm.org/doi/10.1007/s11277-018-5984-y
Zhang WHe HYe SWang ZZheng Q(2018)Enhancing QoE for Mobile Users by Environment-Aware HTTP Adaptive StreamingSensors10.3390/s1811364518:11(3645)Online publication date: 27-Oct-2018
https://doi.org/10.3390/s18113645
Show More Cited By

Index Terms

MASERATI: mobile adaptive streaming based on environmental and contextual information
1. Networks
  1. Network types
    1. Mobile networks
    2. Wireless access networks

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Published In

cover image ACM Conferences

WiNTECH '13: Proceedings of the 8th ACM international workshop on Wireless network testbeds, experimental evaluation & characterization

September 2013

114 pages

ISBN:9781450323642

DOI:10.1145/2505469

General Chairs:
Albert Banchs
University Carlos III and IMDEA Networks, Spain
,
Sunghyun Choi
Seoul National University, Korea

Copyright © 2013 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 ACM 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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SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing

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Association for Computing Machinery

New York, NY, United States

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Published: 30 September 2013

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MobiCom'13

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SIGMOBILE

MobiCom'13: The 19th Annual International Conference on Mobile Computing and Networking

September 30, 2013

Florida, Miami, USA

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WiNTECH '13 Paper Acceptance Rate 11 of 26 submissions, 42%;

Overall Acceptance Rate 63 of 100 submissions, 63%

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Cited By

Elsherbiny HNagib AAbou-zeid HAbbas HHassanein HNoureldin ABin Sediq ABoudreau G(2020)4G LTE Network Data Collection and Analysis along Public Transportation RoutesGLOBECOM 2020 - 2020 IEEE Global Communications Conference10.1109/GLOBECOM42002.2020.9348031(1-6)Online publication date: Dec-2020
https://doi.org/10.1109/GLOBECOM42002.2020.9348031
Cho SKim DKim CJeong KSohn C(2019)360-Degree Video Traffic Reduction Using Cloud Streaming in MobileWireless Personal Communications: An International Journal10.1007/s11277-018-5984-y105:2(635-654)Online publication date: 1-Mar-2019
https://dl.acm.org/doi/10.1007/s11277-018-5984-y
Zhang WHe HYe SWang ZZheng Q(2018)Enhancing QoE for Mobile Users by Environment-Aware HTTP Adaptive StreamingSensors10.3390/s1811364518:11(3645)Online publication date: 27-Oct-2018
https://doi.org/10.3390/s18113645
Sani YMauthe AEdwards C(2017)Adaptive Bitrate Selection: A SurveyIEEE Communications Surveys & Tutorials10.1109/COMST.2017.272524119:4(2985-3014)Online publication date: Dec-2018
https://doi.org/10.1109/COMST.2017.2725241
Gómez DBoronat FMontagud MLuzón CTimmerer C(2016)End-to-end DASH platform including a network-based and client-based adaptive quality switching moduleProceedings of the 7th International Conference on Multimedia Systems10.1145/2910017.2910638(1-4)Online publication date: 10-May-2016
https://dl.acm.org/doi/10.1145/2910017.2910638
Toit JEllefsen IVon Solms S(2016)Bring your own disaster recovery (BYODR)2016 IST-Africa Week Conference10.1109/ISTAFRICA.2016.7530577(1-12)Online publication date: May-2016
https://doi.org/10.1109/ISTAFRICA.2016.7530577
Triki IEl-Azouzi RHaddad M(2016)Anticipating Resource Management and QoE for Mobile Video Streaming under Imperfect Prediction2016 IEEE International Symposium on Multimedia (ISM)10.1109/ISM.2016.0026(93-98)Online publication date: Dec-2016
https://doi.org/10.1109/ISM.2016.0026
Dubin RDvir APele OHadar OKatz IMashiach O(2016)Adaptation logic for HTTP dynamic adaptive streaming using geo-predictive crowdsourcing for mobile usersMultimedia Systems10.1007/s00530-016-0525-624:1(19-31)Online publication date: 1-Aug-2016
https://doi.org/10.1007/s00530-016-0525-6
Bedwell BSlack PGreenhalgh CMase KLangheinrich MGatica-Perez DGellersen HChoudhury TYatani K(2015)Learning from the expertsProceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing10.1145/2750858.2805838(755-766)Online publication date: 7-Sep-2015
https://dl.acm.org/doi/10.1145/2750858.2805838
Wilk SSchönherr SStohr DEffelsberg WGeerts DDe Marez LPauwels CBentley FTimmerer C(2015)EnvDASHProceedings of the ACM International Conference on Interactive Experiences for TV and Online Video10.1145/2745197.2745205(113-118)Online publication date: 3-Jun-2015
https://dl.acm.org/doi/10.1145/2745197.2745205
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