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Bandwidth-aware Prefetching for Proactive Multi-video Preloading and Improved HAS Performance
Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.
University of Saskatchewan, Canada.
NICTA, Australia.
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2015 (English)In: Proceedings of the ACM International Conference on Multimedia (ACM Multimedia), New York, USA: Association for Computing Machinery (ACM), 2015, p. 551-560Conference paper, Published paper (Refereed)
Abstract [en]

This paper considers the problem of providing users playing one streaming video the option of instantaneous and seamless playback of alternative videos. Recommendation systems can easily provide a list of alternative videos, but there is little research on how to best eliminate the startup time for these alternative videos. The problem is motivated by services that want to retain increasingly impatient users, who frequently watch the beginning of multiple videos, before viewing a video to the end. We present the design, implementation, and evaluation of an HTTP-based Adaptive Streaming (HAS) solution that provides careful prefetching and buffer management. We also present the design and evaluation of three fundamental policy classes that provide different tradeoffs between how aggressively new alternative videos are prefetched versus the importance of ensuring high playback quality. We show that our solution allows us to reduce the startup times of alternative videos by an order of magnitude and effectively adapt the quality such as to ensure the highest possible playback quality of the video being viewed. By improving the channel utilization we also address the discrimination problem that HAS clients often suffer from, allowing us to in some cases simultaneously improve the playback quality of the video being viewed and provide the value-added service of allowing instantaneous playback of the prefetched alternative videos.

Place, publisher, year, edition, pages
New York, USA: Association for Computing Machinery (ACM), 2015. p. 551-560
Keywords [en]
HTTP-based adaptive streaming (HAS); Bandwidth-aware prefetching; Multi-video preloading; Seamless playback
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:liu:diva-128168DOI: 10.1145/2733373.2806270ISI: 000387861300064ISBN: 978-1-4503-3459-4 (print)OAI: oai:DiVA.org:liu-128168DiVA, id: diva2:929857
Conference
ACM Multimedia 2015
Available from: 2016-05-20 Created: 2016-05-19 Last updated: 2018-02-06
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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Publisher's full texthttp://dl.acm.org/citation.cfm?id=2806270&CFID=786182214&CFTOKEN=16712080

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Krishnamoorthi, VengatanathanCarlsson, NiklasShahmehri, Nahid

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