Probabilistic analysis and interdependence discovery in the user interactions of a video news on demand service

Garcı́a, Roberto; Pañeda, Xabiel G.; Melendi, David; García, Víctor G.

doi:10.1016/j.comnet.2009.03.011

Cited by 16 publications

(12 citation statements)

References 20 publications

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“…They were collected from the native PPLive client program, which is installed by users on their computers for video watching. Existing methods which measure users' video watching time at the media server by observing the signaling messages received from clients (e.g., [20], [33], [45]) or infer video watching time at the network access side by sniffing clients' traffic (e.g., [21], [32]) cannot capture user watching time in each session accurately. For instance, a streaming client always pre-fetches a certain amount of video content to ensure its local playback continuity under possible network fluctuations [13].…”

Section: B Log Collectionmentioning

confidence: 99%

Measurement and Modeling of Video Watching Time in a Large-Scale Internet Video-on-Demand System

Chen

Zhang

Liu

et al. 2013

IEEE Trans. Multimedia

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Video watching time is a crucial measure for studying user watching behavior in online Internet video-on-demand (VoD) systems. It is important for system planning, user engagement understanding, and system quality evaluation. However, due to the limited access of user data in large-scale streaming systems, a systematic measurement, analysis, and modeling of video watching time is still missing. In this paper, we measure PPLive, one of the most popular commercial Internet VoD systems in China, over a three week period. We collect accurate user watching data of more than 100 million streaming sessions of more than 100 thousand distinct videos. Based on the measurement data, we characterize the distribution of watching time of different types of videos and reveal a number of interesting characteristics regarding the relation between video watching time and various video-related features (including video type, duration, and popularity). We further build a suite of mathematical models for characterizing these relationships. Extensive performance evaluation shows the high accuracy of these models as compared with commonly used data-mining based models. Our measurement and modeling results bring forth important insights for simulation, design, deployment, and evaluation of Internet VoD systems.

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Section: B Log Collectionmentioning

confidence: 99%

Measurement and Modeling of Video Watching Time in a Large-Scale Internet Video-on-Demand System

Chen

Zhang

Liu

et al. 2013

IEEE Trans. Multimedia

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“…Therefore, it was concluded that the introduction of new content seemed to have an influence on θ, and an algorithm was suggested for working out θ every day, due to the fact that the content remained stable during that time. In [11] the regional on-line newspaper "La Nueva España" was studied during a period of six months, from January to June 2007, with more than 300,000 requests over 1,500 videos, where content popularity was characterized with the Mandelbrot function (θ = 1.3; k = 20.85) and a weak correlation between file duration and file popularity was found.…”

Section: Related Workmentioning

confidence: 99%

Video popularity characterization centered on news-on-demand

González-Aparicio¹,

Garcia²,

Brugos³

et al. 2012

IJMA

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“…In this regard, a great deal of system traces should be collected to characterize the user behaviour. Some studies have been carried out to analyze the user behaviour in different VoD streaming services [31,13,9,18,10]. [31] focuses on user behaviour and content access patterns that are based on trace analysis using a large commercial VoD system.…”

Section: Related Workmentioning

confidence: 99%

StrU

Zowj

Dehghan

2012

Proceedings of the 10th International Conference on Advances in Mobile Computing &Amp; Multimedia - MoMM '12

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To enhance the scalability and availability of Video-on-Demand (VoD) services, Peer-to-Peer (P2P) networks are suggested to be used. In contrast to live streaming services, the point of view is asynchronous for each user in VoD streaming services and the VCR operations are supported, as well. These features make the Quality of Service (QoS) of such services over P2P networks highly dependent on user interactions. This paper, aims at providing a desirable QoS for P2P-based VoD streaming services. We employ the user behaviour model to estimate the requests of each peer for a specific time span in the future. This facilitates the parent selection to be more effective. The simulation results show that the proposed system provides higher stability in the multicast overlay, fewer freezes in the playback, and better Quality-of-Experience (QoE) from the end users' sight.

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Probabilistic analysis and interdependence discovery in the user interactions of a video news on demand service

Cited by 16 publications

References 20 publications

Measurement and Modeling of Video Watching Time in a Large-Scale Internet Video-on-Demand System

Measurement and Modeling of Video Watching Time in a Large-Scale Internet Video-on-Demand System

Video popularity characterization centered on news-on-demand

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