Performance evaluation of cooperative peer selection methods for P2P Video-on-Demand

2009 ◽  
Author(s):  
Masatoshi Kawarasaki ◽  
Kei Suzuki
Keyword(s):  
Performance Evaluation ◽  
Video On Demand ◽  
Selection Methods ◽  
Peer Selection ◽  
On Demand

scholarly journals Popularity Prediction of Videos in IPTV Systems

2015 ◽  
Vol 1 (3) ◽  
pp. 385
Author(s):  
Reyhaneh Ghavami ◽  
Alireza Abdollahpouri ◽  
Zhila Bahrami ◽  
Parham Moradi
Keyword(s):  
Neural Network ◽  
Performance Evaluation ◽  
Service Providers ◽  
Video On Demand ◽  
Content Delivery ◽  
Delivery Systems ◽  
On Demand ◽  
Simulation Based ◽  
Popularity Prediction

Video on demand (VoD) service in IPTV is a bandwidth-hungry application. It has been argued that the distribution of popularity of videos can be well measured using a Zipf-like distribution in which top 10% of the videos account for nearly 90% of requests. In this article, we propose a neural network based method to predict the popularity of videos in an IPTV system. The popularity prediction can be used by service providers for video placement in content delivery systems or hierarchical servers and hence it can lead to bandwidth save. Simulation-based performance evaluation of our proposed method confirms a significant accuracy in the prediction of the popularity of the videos.

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