WO2015051846A1 - Lecture en flux continu optimisée adaptative - Google Patents

Lecture en flux continu optimisée adaptative Download PDF

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Publication number
WO2015051846A1
WO2015051846A1 PCT/EP2013/071158 EP2013071158W WO2015051846A1 WO 2015051846 A1 WO2015051846 A1 WO 2015051846A1 EP 2013071158 W EP2013071158 W EP 2013071158W WO 2015051846 A1 WO2015051846 A1 WO 2015051846A1
Authority
WO
WIPO (PCT)
Prior art keywords
video
content
streaming
video content
server
Prior art date
Application number
PCT/EP2013/071158
Other languages
English (en)
Inventor
Ola Andersson
Marcus Nyberg
Original Assignee
Telefonaktiebolaget L M Ericsson (Publ)
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Telefonaktiebolaget L M Ericsson (Publ) filed Critical Telefonaktiebolaget L M Ericsson (Publ)
Priority to PCT/EP2013/071158 priority Critical patent/WO2015051846A1/fr
Publication of WO2015051846A1 publication Critical patent/WO2015051846A1/fr

Links

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L47/00—Traffic control in data switching networks
    • H04L47/10—Flow control; Congestion control
    • H04L47/38—Flow control; Congestion control by adapting coding or compression rate
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L47/00—Traffic control in data switching networks
    • H04L47/10—Flow control; Congestion control
    • H04L47/24—Traffic characterised by specific attributes, e.g. priority or QoS
    • H04L47/2416—Real-time traffic
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L65/00—Network arrangements, protocols or services for supporting real-time applications in data packet communication
    • H04L65/60—Network streaming of media packets
    • H04L65/61—Network streaming of media packets for supporting one-way streaming services, e.g. Internet radio
    • H04L65/612—Network streaming of media packets for supporting one-way streaming services, e.g. Internet radio for unicast
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L65/00—Network arrangements, protocols or services for supporting real-time applications in data packet communication
    • H04L65/60—Network streaming of media packets
    • H04L65/75—Media network packet handling
    • H04L65/752—Media network packet handling adapting media to network capabilities
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L65/00—Network arrangements, protocols or services for supporting real-time applications in data packet communication
    • H04L65/60—Network streaming of media packets
    • H04L65/75—Media network packet handling
    • H04L65/762—Media network packet handling at the source 
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L65/00—Network arrangements, protocols or services for supporting real-time applications in data packet communication
    • H04L65/80—Responding to QoS

Definitions

  • the present application relates to a method of streaming video; a server for streaming video, an apparatus arranged to adapt the bit rate at which a video is streamed, a computer-readable medium, and a server.
  • Video traffic in wireless communication networks is expected to grow rapidly in the coming years. This will increase the demand for video optimization in the network in order to give as many users as good video streaming quality as possible.
  • Adaptive HTTP streaming (AHS) techniques are becoming more and more popular for video services. Adaptive HTTP streaming supports both video on demand and Live video. Unicast is used by default as transport bearer.
  • Adaptive HTTP streaming is a transport technique using existing file formats such as ISO BMFF or MPEG2-TS.
  • Different audio and video codecs are supported such as H.264, MPEG4, AAC, mp3 codecs.
  • Adaptive HTTP Streaming solutions such as Apple HTTP Live Streaming (HLS), Microsoft SmoothStreaming (IIS), 3GP-DASH, MPEG-DASH, OITV HAS, Adobe Dynamic Streaming and more.
  • HLS Apple HTTP Live Streaming
  • IIS Microsoft SmoothStreaming
  • 3GP-DASH 3GP-DASH
  • MPEG-DASH 3GP-DASH
  • OITV HAS Adobe Dynamic Streaming
  • Dynamic Adaptive Streaming over HTTP also known as MPEG- DASH
  • MPEG-DASH enables high quality streaming of media content over the Internet delivered from conventional HTTP web servers.
  • MPEG-DASH works by breaking the content into a sequence of small HTTP-based file segments, each segment containing a short interval of playback time of a content that is potentially many hours in duration, such as a movie or the live broadcast of a sports event.
  • the content is made available at a variety of different bit rates, by way of alternative segments encoded at different bit rates and covering aligned short intervals of play back time.
  • the client automatically selects from the alternatives the next segment to download and play back based on current network
  • an MPEG-DASH client can seamlessly adapt to changing network conditions, and provide high quality play back without stalls or rebuffering events.
  • AHS and DASH are selfish protocols in so far as each client tries to take as good video quality as it possibly can and without any regard for other clients in the same network. This means that networks can quickly reach capacity with a few clients streaming content at high quality.
  • the inventors have realized that adaptive streaming techniques are likely to deliver a streaming quality to a client that is greater than is needed to satisfy the user of that client.
  • the methods and apparatus described herein allow a service provider to adapt the streaming quality dependent upon the nature of the content being streamed.
  • the method comprises receiving a streaming request for video content, and determining a content type of the requested video content.
  • the method further comprises adapting the bit rate at which the video is streamed dependent upon the content type.
  • the determined content type of the requested video content may be: the playback position of the video content; whether the video content is live; a content category of the video content; metadata associated with the video content; a user's content preferences; or a user's historical viewing data.
  • the method may adjust the video quality based on where in the content the playback position is.
  • the method may adjust the video quality based on what type of content the user is watching. This may be done with or without user statistics about preferred content.
  • the playback position may be a relative playback position.
  • the playback position may be relative to a total length of a video asset or program.
  • the video may be streamed over a network, and the method may further comprise making a determination of the network congestion, and if the network is congested then adapting the bit rate at which the video is streamed dependent upon the video content If the video content is a movie and the playback position exceeds a threshold proportion of the total length of the movie, then the streaming quality may be reduced.
  • the Segment Adjustment Function can help optimizing the number of ongoing streaming sessions.
  • the streaming quality may be reduced.
  • the streaming quality may be reduced by one step.
  • the engagement of viewers of a live sporting event can be expected to be very high, and as such the viewers are less likely to accept any interruption in the video.
  • the streaming can be optimized by using a slightly lower quality to reduce the likelihood of rebuffering.
  • a server for streaming video to at least one client device the server arranged to: receive a streaming request for video content; determine a content type of the requested video content; and adapt the bit rate at which the video is streamed dependent upon the content type.
  • the determined content type of the requested video content may be: the playback position of the video content; whether the video content is live; a content category of the video content; metadata associated with the video content; a user's content preferences; or a user's historical viewing data.
  • the server may adjust the video quality based on where in the content the playback position is.
  • the server may adjust the video quality based on what type of content the user is watching. This may be done with or without user statistics about preferred content.
  • the playback position may be a relative playback position.
  • the playback position may be relative to a total length of a video asset or program.
  • the server may be further arranged to receive an indication of how congested the network is, and if the network is congested then the server may be arranged to adapt the bit rate at which the video is streamed dependent upon the video content
  • an apparatus arranged to adapt the bit rate at which a video is streamed dependent upon the content type, the apparatus comprising a processor and a memory.
  • the memory containing instructions executable by said processor.
  • the apparatus is operative to: receive a streaming request for video content and determine a content type of the requested video content.
  • the apparatus is further operative to adapt the bit rate at which the video is streamed dependent upon the content type.
  • the computer program product may be in the form of a nonvolatile memory or volatile memory, e.g. an EEPROM (Electrically Erasable Programmable Read-only Memory), a flash memory, a disk drive or a RAM (Random-access memory).
  • a server comprising a processor and memory, said memory containing instructions executable by said processor whereby said server is operative to receive a streaming request for video content and determine a content type of the requested video content. The server further operative to adapt the bit rate at which the video is streamed dependent upon the content type.
  • Figure 1 shows a simplified example of an adaptive bit rate streaming system
  • Figure 2 illustrates a method of streaming video
  • Figure 3 illustrates a further method for streaming video
  • Figure 4 illustrates how the streaming quality of a movie can be adapted
  • Figure 5 illustrates how the streaming quality of a sports event can be adapted
  • Figure 6 shows the components of a web server. Detailed description
  • a network can quickly reach capacity with a few clients streaming content at high quality.
  • Adaptive streaming protocols are selfish protocols in so far as each client tries to take as good video quality as it possibly can and without any regard for other clients in the same network. This has the result that some clients get a better video quality than they really would need: that is, often the client receives content at a streaming quality higher than needed to satisfy the users of these clients. Further, if some existing users receive a lower quality stream in a network operating at capacity then that network would be able to serve additional clients, in providing streaming services or other services.
  • the methods and apparatus described herein provide a way to "downgrade" the video quality in a safe way when needed. This is done by lowering the quality while minimizing the risk of lowering the quality too much so that users are dissatisfied and leave the service.
  • a plurality of different factors affect user perceived video quality (resolution, frame rate, quantization factor, colour depth, etc .).
  • the greater the bitrate at which the video is encoded the greater its quality will be.
  • the greater the bandwidth there is available in a system the greater the video quality that can be carried.
  • the video quality is optimized for a certain bitrate.
  • the number of streams a network can handle is maximized by establishing a minimum bandwidth needed to give an acceptable quality for each stream. This allows the system to serve as many users as possible.
  • FIG. 1 shows a simplified example of an adaptive bit rate streaming system 100.
  • a web server 1 10 is responsible for serving a plurality of client devices 140,141 ,142 with Adaptive HTTP Streaming video segments.
  • the webserver 1 10 comprises a media server 1 12, a segment adjustment function 1 14, and data storage 1 16.
  • Data storage 1 16 stores video segments of a video at three quality levels, or bitrates, A, B and C, corresponding to high, medium and low quality respectively.
  • the Segment Adjustment Function 1 14 analyzes the Q value and uses the P values in order to adjust the Q values (if necessary) before forwarding the request to the Media Server 1 12.
  • the Segment Adjustment Function 1 14 determines if the requested quality should be kept or if the quality can be lowered. The exact algorithms for making this judgment can be created in many different ways; some examples are given herein.
  • Segment Adjustment Function 1 14 can function.
  • the Segment Adjustment Function 1 14 In the first mode the Segment Adjustment Function 1 14 has no notion about the congestion state of the network over which the video content is streamed. In this mode the Segment Adjustment Function 1 14 maintains constant control over the media streaming quality. A drawback with this mode is that it can result in unnecessary lowering of the media quality, for example in the situation of a client device comprising a UE in a cellular communication network and where the client device is alone in a cell.
  • the Segment Adjustment Function 1 14 is connected to a network monitoring function (which is standard network equipment in many networks, such as a cellular communication network).
  • a network monitoring function which is standard network equipment in many networks, such as a cellular communication network.
  • Adjustment Function 1 14 can then be arranged to only control the media streaming quality when the cell is congested.
  • the Segment Adjustment Function 1 14 controls the media streaming quality
  • the streaming quality is adjusted dependent upon the content type of the streamed media.
  • Figure 2 illustrates a method of streaming video.
  • the method comprises receiving 210 a streaming request for video content.
  • the content type of the requested video content is determined 220.
  • the bit rate at which the video is streamed is adapted 230 dependent upon the content type.
  • Figure 3 illustrates a further method for streaming video.
  • the method further comprises making a determination of the network congestion, and if the network is congested then adapting the bit rate at which the video is streamed dependent upon the video content.
  • the method comprises receiving 310 a streaming request for video content.
  • a determination is made 315 as to how congested the network is. If the network congestion measure does not exceed a threshold value, then no adjustment of the video streaming quality is made and the requested content is streamed 350. However, if the network congestion measure does exceed a threshold value, then, the content type of the requested video content is determined 320.
  • the bit rate at which the video is streamed is adapted 330 dependent upon the content type, and the video is streamed 340 at the adapted streaming quality.
  • One aspect of content type that can be used to determine streaming quality is the playback position of a program or video asset. The playback position of a video affects the minimum acceptable quality a user will accept.
  • Unacceptable streaming quality may cause a user to stop streaming the video. For example, if the user has watched a large part of a movie
  • the Segment Adjustment Function can help optimizing the number of ongoing streaming sessions.
  • the lower curve 410 illustrates the minimum quality acceptable to a viewer. This begins at around 75% and decreases as the movie progresses. Towards the end of the film the user will accept a lower streaming quality before switching off, because they will want to see how the movie concludes. Clearly, it will be preferable to provide the viewer with best quality available, but in the context of a network becoming more congested over the duration of a movie being streamed, a user will generally prefer a lower quality stream as opposed to no stream at all.
  • the target quality level 420 decreases step wise, each step corresponding to a drop to the next lowest quality level available over adaptive bitrate streaming.
  • Figure 5 shows an alternative example in the context of a sporting event.
  • the Segment Adjustment Function can also help in optimizing the final period of streaming sessions by implementing a slightly lower target quality 540 towards the end of the sporting event. This results in a bit rate that requires less than a maximum available bandwidth, which minimizes the likelihood of rebuffering being required in response to changing network conditions.
  • Another aspect of content type that can be used to determine streaming quality is the importance of the current scene. The importance may be measured as an expected level of user interest.
  • a movie may be indexed before it is streamed, the indexing rating the importance of each section of the film.
  • the low importance sections are then given a lower target bitrate making them eligible for a quality drop.
  • the indexing may be performed manually, or automatically. In the latter case, an algorithm to detect level of visual action may be used to determine the importance of each scene. Alternatively, the results from test screenings may be used to determine the importance of each scene.
  • content such as a news program, it may be considered to be appropriate to have higher quality during video reports than during the periods of talking heads, the latter being appropriate for a quality drop.
  • the content type of such a news program may be determined manually, or by use of a content recognition algorithm. Different types of content have different characteristics when it comes to attracting viewers.
  • the Segment Adjustment Function is arranged to take into account such content characteristics in order to determine the popularity of the requested content.
  • the Segment Adjustment Function may receive user specific content preferences from the client, or from a database of user activity.
  • user specific content preferences may comprise: user x watches sport 75% of his time, horror movies 10%, etc..
  • the components of a web server 1 10 are illustrated in figure 6.
  • the web server comprises a processor 620, a memory 625, data storage 630, and a network interface 640.
  • the processor 620 is arranged to receive instructions which, when executed, causes the processor 620 to carry out the above described method.
  • the instructions may be stored on the memory 625.
  • Data storage 630 contains the various different versions of videos available for streaming.
  • Network interface 640 allows the web server to communicate with a network over which the video content is streamed to at least one client device. Through network interface 640, the web server can query a network congestion monitor node to establish the congestion status of the network.

Landscapes

  • Engineering & Computer Science (AREA)
  • Multimedia (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Two-Way Televisions, Distribution Of Moving Picture Or The Like (AREA)

Abstract

L'invention concerne un procédé de lecture vidéo en flux continu. Le procédé consiste à recevoir une demande de lecture en flux continu d'un contenu vidéo et à déterminer un type de contenu du contenu vidéo demandé. Le procédé consiste en outre à adapter le débit binaire auquel la vidéo est lue en flux continu en fonction du type de contenu. En adaptant la qualité de lecture en flux continu en fonction du contenu vidéo qui est lu en flux continu, un utilisateur peut obtenir un contenu à une qualité déterminée de sorte qu'il y ait des chances qu'elle soit acceptable par cet utilisateur tout en utilisant un minium de ressources réseau. Ainsi, on obtient un procédé de lecture en flux continu optimisé par le réseau.
PCT/EP2013/071158 2013-10-10 2013-10-10 Lecture en flux continu optimisée adaptative WO2015051846A1 (fr)

Priority Applications (1)

Application Number Priority Date Filing Date Title
PCT/EP2013/071158 WO2015051846A1 (fr) 2013-10-10 2013-10-10 Lecture en flux continu optimisée adaptative

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/EP2013/071158 WO2015051846A1 (fr) 2013-10-10 2013-10-10 Lecture en flux continu optimisée adaptative

Publications (1)

Publication Number Publication Date
WO2015051846A1 true WO2015051846A1 (fr) 2015-04-16

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2018060488A1 (fr) * 2016-09-30 2018-04-05 British Telecommunications Public Limited Company Distribution à débit binaire adaptatif en fonction de l'importance pour la personne qui visionne
WO2018060489A1 (fr) * 2016-09-30 2018-04-05 British Telecommunications Public Limited Company Distribution à débit binaire adaptatif en fonction de l'importance pour la personne qui visionne

Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20130254341A1 (en) * 2012-03-23 2013-09-26 Cisco Technology, Inc. Network assisted rate shifting for adaptive bit rate streaming

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20130254341A1 (en) * 2012-03-23 2013-09-26 Cisco Technology, Inc. Network assisted rate shifting for adaptive bit rate streaming

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
ASIYA KHAN ET AL: "QoE Prediction Model and its Application in Video Quality Adaptation Over UMTS Networks", IEEE TRANSACTIONS ON MULTIMEDIA, IEEE SERVICE CENTER, PISCATAWAY, NJ, US, vol. 14, no. 2, 1 April 2012 (2012-04-01), pages 431 - 442, XP011436300, ISSN: 1520-9210, DOI: 10.1109/TMM.2011.2176324 *
JIASI CHEN ET AL: "QAVA", EMERGING NETWORKING EXPERIMENTS AND TECHNOLOGIES, ACM, 2 PENN PLAZA, SUITE 701 NEW YORK NY 10121-0701 USA, 10 December 2012 (2012-12-10), pages 121 - 132, XP058010427, ISBN: 978-1-4503-1775-7, DOI: 10.1145/2413176.2413191 *

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2018060488A1 (fr) * 2016-09-30 2018-04-05 British Telecommunications Public Limited Company Distribution à débit binaire adaptatif en fonction de l'importance pour la personne qui visionne
WO2018060489A1 (fr) * 2016-09-30 2018-04-05 British Telecommunications Public Limited Company Distribution à débit binaire adaptatif en fonction de l'importance pour la personne qui visionne
WO2018060490A1 (fr) * 2016-09-30 2018-04-05 British Telecommunications Public Limited Company Distribution à débit binaire adaptatif en fonction de l''importance pour la personne qui visionne
US10931993B2 (en) 2016-09-30 2021-02-23 British Telecommunications Public Limited Company Viewer importance adaptive bit rate delivery
US11044507B2 (en) 2016-09-30 2021-06-22 British Telecommunications Public Limited Company Viewer importance adaptive bit rate delivery
US11317171B2 (en) 2016-09-30 2022-04-26 British Telecommunications Public Limited Company Viewer importance adaptive bit rate delivery

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