A Survey of User Behavior in VoD Service and Bandwidth-Saving Multicast Streaming Schemes

Choi, Joonho; Reaz, Abu; Mukherjee, Biswanath

doi:10.1109/surv.2011.030811.00051

Cited by 107 publications

(36 citation statements)

References 59 publications

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“…With the length of the transmitted video part decreasing, the number of frames that a library frame is referenced by also decreases. practice, 29,30 the proposed scheme is still valuable for VOD streaming application.…”

Section: Discussion Of Random Accessmentioning

confidence: 99%

Scene-library-based video coding scheme exploiting long-term temporal correlation

Zuo

et al. 2017

J. Electron. Imaging

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, "Scene-library-based video coding scheme exploiting long-term temporal correlation," J. Electron. Imaging 26(4), 043026 (2017), doi: 10.1117/1.JEI.26.4.043026. Abstract. In movies and TV shows, it is common that several scenes repeat alternately. These videos are characterized with the long-term temporal correlation, which can be exploited to improve video coding efficiency. However, in applications supporting random access (RA), a video is typically divided into a number of RA segments (RASs) by RA points (RAPs), and different RASs are coded independently. In such a way, the long-term temporal correlation among RASs with similar scenes cannot be used. We present a scene-library-based video coding scheme for the coding of videos with repeated scenes. First, a compact scene library is built by clustering similar scenes and extracting representative frames in encoding video. Then, the video is coded using a layered scene-library-based coding structure, in which the library frames serve as long-term reference frames. The scene library is not cleared by RAPs so that the long-term temporal correlation between RASs from similar scenes can be exploited. Furthermore, the RAP frames are coded as interframes by only referencing library frames so as to improve coding efficiency while maintaining RA property. Experimental results show that the coding scheme can achieve significant coding gain over state-of-the-art methods. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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Section: Discussion Of Random Accessmentioning

confidence: 99%

Scene-library-based video coding scheme exploiting long-term temporal correlation

Zuo

et al. 2017

J. Electron. Imaging

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“…The server considers this information as playback logs and analyzes these logs to be aware of the condition of request and playback of resources such as the file popularity and the mean playback time of video files. The popularities of items in follow a Zipf distribution [26,27] and the popularity value of each file can be obtained according to…”

Section: Idvd Detailed Designmentioning

confidence: 99%

A Novel Interest Detection-Based Video Dissemination Algorithm under Flash Crowd in Mobile Ad Hoc Networks

Jia

Jiang

et al. 2015

International Journal of Distributed Sensor Networks

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The peer-to-peer-based video resource dissemination is important for handling extreme conditions such as flash crowds which severely break the balance between supply and demand of video content and bring negative effects for quality of service (QoS). In this paper, we propose a novel interest detection-based video dissemination algorithm under flash crowd in mobile ad hoc networks (IDVD). IDVD classifies the user behavior of requesting video content in terms of the popularities and playback time of video and considers the demand of popular video as the cause of flash crowd. IDVD makes use of the prediction of necessary bandwidth and period time of intensive request to be aware of period time and scale of flash crowd. IDVD employs a resource dissemination algorithm which can fast discover interested nodes and achieve the on-demand dissemination of video resources in neighboring geographical area, in order to handle imbalance between supply and demand. IDVD uses the epidemic model to describe the state transition of nodes and define the convergence condition of resource dissemination algorithm. Extensive tests show how IDVD achieves much better performance results in comparison with other state of the art solutions.

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“…In contrast, we model user behavior and access patterns for a large-scale IPTV system using large volume of real user data. Recent studies on user behaviors of CDN IPTV networks have focused independently on either live TV [Sripanidkulchai et al 2004;Veloso et al 2006;Agrawal et al 2007;Cha et al 2008;Qiu et al 2009bQiu et al , 2009a or VoD [Cherkasova and Gupta 2004;Yu et al 2006;Cheng et al 2008;Choi et al 2012;Abrahamsson and Bjorkman 2013]. One of the first measurement studies is Yu et al [2006], where the authors studied the traces of a large CDN VoD system and introduced a modified Poisson distribution that more accurately modeled the user arrival process.…”

Section: Related Workmentioning

confidence: 99%

“…In comparison, live channels are much better modeled by a geometric distribution. Therefore, Zipf distribution as commonly assumed in literatures should be used judiciously [Yu et al 2006;Qiu et al 2009b;Choi et al 2012]. VoD file popularity is much more "volatile" as compared with the popularity of live channels, especially for those popular files which may drop quite fast over a month.…”

Section: Introductionmentioning

confidence: 99%

Dissecting User Behaviors for a Simultaneous Live and VoD IPTV System

Liu

Cui

Chan

et al. 2014

ACM Trans. Multimedia Comput. Commun. Appl.

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IPTV services deployed nowadays often consist of both live TV and Video-on-Demand (VoD), offered by the same service provider to the same pool of users over the same managed network. Understanding user behaviors in such a setting is hence an important step for system modelling and optimization. Previous studies on user behavior on video services were on either live TV or VoD.For the first time, we conduct an in-depth large-scale behavior study for IPTV users offering simultaneously live TV and VoD choices at the same time. Our data is from the largest IPTV service provider in China, offering hundreds of live channels and hundreds of thousands of VoD files, with traces covering more than 1.9 million users over a period of 5 months. This large dataset provides us a unique opportunity to cross-compare user viewing behaviors for these services on the same platform, and sheds valuable insights on how users interact with such a simultaneous system.Our results lead to new understanding on IPTV user behaviors which have strong implications on system design. For example, we find that the average holding time for VoD is significantly longer than live TV. live TV users tend to surf more. However, if such channel surfing is discounted, the holding times of both services are not much different. While users in VoD tend to view HD longer, channel popularity for live TV is much less dependent on its video quality. In contrast to some popular assumptions on user interactivity, the transitions among live TV, VoD, and offline modes are far from a Markov model.

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A Survey of User Behavior in VoD Service and Bandwidth-Saving Multicast Streaming Schemes

Cited by 107 publications

References 59 publications

Scene-library-based video coding scheme exploiting long-term temporal correlation

Scene-library-based video coding scheme exploiting long-term temporal correlation

A Novel Interest Detection-Based Video Dissemination Algorithm under Flash Crowd in Mobile Ad Hoc Networks

Dissecting User Behaviors for a Simultaneous Live and VoD IPTV System

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