Individual Preference Probability Modeling and Parameterization for Video Content in Wireless Caching Networks

Ming Chun Lee*, Andreas F. Molisch, Nishanth Sastry, Aravindh Raman

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

Caching of video files at the wireless edge, i.e., at the base stations or on user devices, is a key method for improving wireless video delivery. While global popularity distributions of video content have been investigated in the past and used in a variety of caching algorithms, this paper investigates the statistical modeling of the individual user preferences. With individual preferences being represented by probabilities, we identify their critical features and parameters and propose a novel modeling framework by using a genre-based hierarchical structure as well as a parameterization of the framework based on an extensive real-world data set. Besides, the correlation analysis between parameters and critical statistics of the framework is conducted. With the framework, an implementation recipe for generating practical individual preference probabilities is proposed. By comparing with the underlying real data, we show that the proposed models and generation approach can effectively characterize the individual preferences of users for video content.

Original languageEnglish
Article number8667721
Pages (from-to)676-690
Number of pages15
JournalIEEE/ACM Transactions on Networking
Volume27
Issue number2
DOIs
StatePublished - Apr 2019

Keywords

  • caching networks
  • modeling and parameterization
  • User preference
  • video content delivery

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