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Empowering the creative user: personalized HTTP-based adaptive streaming of multi-path nonlinear video
Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
Linköping University, Department of Computer and Information Science. Linköping University, The Institute of Technology.
Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, The Institute of Technology.
University of Saskatchewan.
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2013 (English)In: FhMN '13 Proceedings of the 2013 ACM SIGCOMM workshop on Future human-centric multimedia networking, New York, USA: Association for Computing Machinery (ACM), 2013, p. 53-58Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents the design, implementation, and validation of a novel system that supports streaming and playout of personalized, multi-path, nonlinear video. In contrast to regular video, in which the file content is played sequentially, our design allows multiple nonlinear video sequences of the underlying (linear) video to be stitched together and played in any personalized order, and clients can be provided multiple path choices. The design combines the ideas of HTTP-based adaptive streaming (HAS) and multi-path nonlinear video. Personalization of the content is achieved with the use of a customized metafile, which is downloaded separately from the underlying media and the manifest file that defines the HAS structure. An extension to the user interface allows path choices to be presented to and made by the user. Novel buffer management and prefetching policies are used to ensure seamless uninterrupted playback regardless of client path choices, even under scenarios in which clients defer their choices until the last possible moment. Our solution allows creative home users to easily create their own multi-path nonlinear video, opening the door to an endless possibility of new opportunities and media forms.

Place, publisher, year, edition, pages
New York, USA: Association for Computing Machinery (ACM), 2013. p. 53-58
Keyword [en]
HTTP-based adaptive streaming, Multi-path video, Nonlinear video, Seamless playback
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:liu:diva-96695DOI: 10.1145/2491172.2491183ISBN: 978-1-4503-2183-9 (print)OAI: oai:DiVA.org:liu-96695DiVA, id: diva2:642910
Conference
ACM SIGCOMM 2013, Hong Kong, China, 12-16 August 2013
Note

Nominated as the Best Paper in the 2013 ACM SIGCOMM workshop on Future human-centric Multimedia Networking (FhMN)

Available from: 2013-08-23 Created: 2013-08-23 Last updated: 2018-02-06Bibliographically approved
In thesis
1. Efficient HTTP-based Adaptive Streaming of Linear and Interactive Videos
Open this publication in new window or tab >>Efficient HTTP-based Adaptive Streaming of Linear and Interactive Videos
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Online video streaming has gained tremendous popularity over recent years and currently constitutes the majority of Internet traffic. As large-scale on-demand streaming continues to gain popularity, several important questions and challenges remain unanswered. This thesis addresses open questions in the areas of efficient content delivery for HTTP-based Adaptive Streaming (HAS) from different perspectives (client, network and content provider) and in the design, implementation, and evaluation of interactive streaming applications over HAS.

As streaming usage scales and new streaming services emerge, continuous improvements are required to both the infrastructure and the techniques used to deliver high-quality streams. In the context of Content Delivery Network (CDN) nodes or proxies, this thesis investigates the interaction between HAS clients and proxy caches. In particular, we propose and evaluate classes of content-aware and collaborative policies that take advantage of information that is already available, or share information among elements in the delivery chain, where all involved parties can benefit. Asides from the users’ playback experience, it is also important for content providers to minimize users’ startup times. We have designed and evaluated different classes of client-side policies that can prefetch data from the videos that the users are most likely to watch next, without negatively affecting the currently watched video. To help network providers to monitor and ensure that their customers enjoy good playback experiences, we have proposed and evaluated techniques that can be used to estimate clients’ current buffer conditions. Since several services today stream over HTTPS, our solution is adapted to predict client buffer conditions by only observing encrypted network-level traffic. Our solution allows the operator to identify clients with low-buffer conditions and implement policies that help avoid playback stalls.

The emergence of HAS as the de facto standard for delivering streaming content also opens the door to use it to deliver the next generation of streaming services, such as various forms of interactive services. This class of services is gaining popularity and is expected to be the next big thing in entertainment. For the area of interactive streaming, this thesis proposes, models, designs, and evaluates novel streaming applications such as interactive branched videos and multi-video stream bundles. For these applications, we design and evaluate careful prefetching policies that provides seamless playback (without stalls or switching delay) even when interactive branched video viewers defer their choices to the last possible moment and when users switches between alternative streams within multi-video stream bundles. Using optimization frameworks, we design and implement effective buffer management techniques for seamless playback experiences and evaluate several tradeoffs using our policies.  

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2018. p. 72
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1902
National Category
Computer Sciences
Identifiers
urn:nbn:se:liu:diva-143802 (URN)10.3384/diss.diva-143802 (DOI)9789176853719 (ISBN)
Public defence
2018-03-13, Ada Lovelace, B-huset, Campus Valla, Linköping, 13:15 (English)
Opponent
Supervisors
Funder
CUGS (National Graduate School in Computer Science)Swedish Research Council
Available from: 2018-02-12 Created: 2018-02-06 Last updated: 2018-02-13Bibliographically approved

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Krishnamoorthi, VengatanathanCarlsson, NiklasShahmehri, Nahid
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