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Analysis of user experience and behavior in wireless streaming video viewing

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TitleInfo
Title
Analysis of user experience and behavior in wireless streaming video viewing
Name (type = personal)
NamePart (type = family)
Deng
NamePart (type = given)
Hua
NamePart (type = date)
1988
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Hua Deng
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author
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Lindqvist
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Janne
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Janne Lindqvist
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Advisory Committee
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chair
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Wade
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Wade Trappe
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Advisory Committee
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internal member
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Howard
NamePart (type = given)
Richard
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Richard Howard
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Advisory Committee
Role
RoleTerm (authority = RULIB)
internal member
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NamePart (type = family)
Ylä-Jääski
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Antti
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Antti Ylä-Jääski
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Advisory Committee
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outside member
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Rutgers University
Role
RoleTerm (authority = RULIB)
degree grantor
Name (type = corporate)
NamePart
School of Graduate Studies
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school
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Text
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theses
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2020
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2020-10
Language
LanguageTerm (authority = ISO 639-3:2007); (type = text)
English
Abstract
Online streaming is one of the most popular services available over the Internet. Today video is increasingly consumed over wireless networks with their far higher packet loss rate compared with wired networks. It generates video impairments that degrade user experience.

We studied video impairments caused by packet losses with a realistic setting. We found that viewers prefer high-resolution videos with some impairments to smooth low-resolution videos. It disagrees with the HTTP adaptive streaming protocol, which sacrifices resolution for smoothness. Additionally, viewers ignore some short impairments and feel that block-artifacts impairment occurring after a freeze is acceptable. We are the first to reveal that impairment occurrence order and inter-impairment interval length influence user experience differently. These findings show the feasibility of improving user experience by reordering and balancing impairment occurrences.

In addition, we conducted experiments on observing users streaming video viewing behaviors under packet loss wireless networks. We have observed nine types of behaviors including system level behaviors and video player level behaviors. We noticed that low video quality and perceivable video impairments are key factors to motivate users take actions and users usually choose behaviors they believe can improve viewing experience. Also, the sequence of behaviors user has taken follows some particular orders. According to these observations, we propose a novel user video watching behavior prediction model that achieves 94.7% accuracy. Moreover, we created cognitive models that explain how video quality variations and human memories play roles in users’ behavior decision making. Findings show the feasibility of improving user experience by reordering and balancing impairment occurrences.

Our study results and the user behavior prediction model provide promising ideas and tools for enhancing user experience under crowded networks where video impairments are unavoidable and optimizing network resource and user management via human engineering.
Subject (authority = local)
Topic
Online video streaming
Subject (authority = RUETD)
Topic
Electrical and Computer Engineering
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Title
Rutgers University Electronic Theses and Dissertations
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ETD_11146
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Extent
1 online resource (xiii, 99 pages)
Note (type = degree)
Ph.D.
Note (type = bibliography)
Includes bibliographical references
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ETD doctoral
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Title
School of Graduate Studies Electronic Theses and Dissertations
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rucore10001600001
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NjNbRU
Identifier (type = doi)
doi:10.7282/t3-8zy8-ev39
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Rights

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The author owns the copyright to this work.
RightsHolder (type = personal)
Name
FamilyName
Deng
GivenName
Hua
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime (encoding = w3cdtf); (qualifier = exact); (point = start)
2020-09-14 08:57:05
AssociatedEntity
Name
Hua Deng
Role
Copyright holder
Affiliation
Rutgers University. School of Graduate Studies
AssociatedObject
Type
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Author Agreement License
Detail
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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Technical

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2020-09-14T14:37:34
DateCreated (point = end); (encoding = w3cdtf); (qualifier = exact)
2020-09-14T14:37:34
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