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How much can large-scale video-on-demand benefit from users' cooperation?

Authors:

Valentina Martina,

Michele Garetto,

Emilio LeonardiAuthors Info & Claims

IEEE/ACM Transactions on Networking (TON), Volume 23, Issue 6

Pages 1846 - 1861

https://doi.org/10.1109/TNET.2014.2346077

Published: 01 December 2015 Publication History

Abstract

We propose an analytical framework to tightly characterize the scaling laws for the additional bandwidth that servers must supply to guarantee perfect service in peer-assisted Video-on-Demand systems, taking into account essential aspects such as peer churn, bandwidth heterogeneity, and Zipf-like video popularity. Our results reveal that the catalog size and the content popularity distribution have a huge effect on the system performance. We show that users' cooperation can effectively reduce the servers' burden for a wide range of system parameters, confirming to be an attractive solution to limit the costs incurred by content providers as the system scales to large populations of users.

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Cited By

Hassanpour MHoseinitabatabaei SBarnaghi PTafazolli R(2020)Improving the Accuracy of the Video Popularity Prediction Models through User Grouping and Video Popularity ClassificationACM Transactions on the Web10.1145/337249914:1(1-28)Online publication date: 7-Feb-2020
https://dl.acm.org/doi/10.1145/3372499
Zhao HWang JWang QLiu F(2019)Queue-based and learning-based dynamic resources allocation for virtual streaming media server cluster of multi-version VoD systemMultimedia Tools and Applications10.1007/s11042-019-7457-z78:15(21827-21852)Online publication date: 1-Aug-2019
https://dl.acm.org/doi/10.1007/s11042-019-7457-z
Machanick PMasinde M(2017)Video on demand in a high bandwidth worldProceedings of the South African Institute of Computer Scientists and Information Technologists10.1145/3129416.3129424(1-8)Online publication date: 26-Sep-2017
https://dl.acm.org/doi/10.1145/3129416.3129424
Show More Cited By

How much can large-scale video-on-demand benefit from users' cooperation?
1. General and reference
  1. Cross-computing tools and techniques
2. Software and its engineering
  1. Software organization and properties
    1. Software system structures

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Information & Contributors

Information

Published In

cover image IEEE/ACM Transactions on Networking

IEEE/ACM Transactions on Networking Volume 23, Issue 6

December 2015

306 pages

ISSN:1063-6692

Editor:
R. Srikant
Univ. Illinois at Urbana-Champaign, Urbana, IL

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Publisher

IEEE Press

Publication History

Published: 01 December 2015

Published in TON Volume 23, Issue 6

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Cited By

Hassanpour MHoseinitabatabaei SBarnaghi PTafazolli R(2020)Improving the Accuracy of the Video Popularity Prediction Models through User Grouping and Video Popularity ClassificationACM Transactions on the Web10.1145/337249914:1(1-28)Online publication date: 7-Feb-2020
https://dl.acm.org/doi/10.1145/3372499
Zhao HWang JWang QLiu F(2019)Queue-based and learning-based dynamic resources allocation for virtual streaming media server cluster of multi-version VoD systemMultimedia Tools and Applications10.1007/s11042-019-7457-z78:15(21827-21852)Online publication date: 1-Aug-2019
https://dl.acm.org/doi/10.1007/s11042-019-7457-z
Machanick PMasinde M(2017)Video on demand in a high bandwidth worldProceedings of the South African Institute of Computer Scientists and Information Technologists10.1145/3129416.3129424(1-8)Online publication date: 26-Sep-2017
https://dl.acm.org/doi/10.1145/3129416.3129424
Ma GWang ZZhang MYe JChen MZhu W(2017)Understanding Performance of Edge Content Caching for Mobile Video StreamingIEEE Journal on Selected Areas in Communications10.1109/JSAC.2017.268095835:5(1076-1089)Online publication date: 23-May-2017
https://dl.acm.org/doi/10.1109/JSAC.2017.2680958

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