Statistical characterization of a real video on demand service: User behaviour and streaming-media workload analysis
The video on demand service characterized in this article has surpassed 4 years of service, and the access log database stores information of more than 160,000 reproductions and 900 videos. The wide variety of subjects, the range of content lengths and a frequent update of contents (several new vide...
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Published in | Simulation modelling practice and theory Vol. 15; no. 6; pp. 672 - 689 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
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Elsevier B.V
01.07.2007
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ISSN | 1569-190X 1878-1462 |
DOI | 10.1016/j.simpat.2007.02.004 |
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Abstract | The video on demand service characterized in this article has surpassed 4 years of service, and the access log database stores information of more than 160,000 reproductions and 900 videos. The wide variety of subjects, the range of content lengths and a frequent update of contents (several new videos every day), clearly differentiate this study from other previous research limited to specific users, subjects or environments. We present a statistical study of user behaviour and streaming traffic, analyzing session characteristics, mistaken reproductions, amount of media delivered, number and length of pauses and jumps in the reproduction, popularity and daily access profile. The results of the analysis will allow us to develop simulation models and workload generators to evaluate different scenarios and situations of the service. |
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AbstractList | The video on demand service characterized in this article has surpassed 4 years of service, and the access log database stores information of more than 160,000 reproductions and 900 videos. The wide variety of subjects, the range of content lengths and a frequent update of contents (several new videos every day), clearly differentiate this study from other previous research limited to specific users, subjects or environments. We present a statistical study of user behaviour and streaming traffic, analyzing session characteristics, mistaken reproductions, amount of media delivered, number and length of pauses and jumps in the reproduction, popularity and daily access profile. The results of the analysis will allow us to develop simulation models and workload generators to evaluate different scenarios and situations of the service. |
Author | Vilas, Manuel García, Roberto García, Victor Melendi, David Pañeda, Xabiel G. |
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Cites_doi | 10.1145/505237.505239 10.1007/s11042-006-0040-4 10.1145/988672.988744 10.1145/1005847.1005868 10.1145/641007.641020 10.1145/378344.378348 10.1117/12.373516 10.1145/637219.637220 10.1145/1028788.1028795 10.1145/505237.505238 10.1145/507553.507554 10.1109/INFCOM.2000.832178 10.1007/3-540-36166-9_2 10.1145/776322.776327 10.1117/12.473407 |
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Keywords | Video on demand Network traffic measurement Workload characterization Multimedia streaming |
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Title | Statistical characterization of a real video on demand service: User behaviour and streaming-media workload analysis |
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