ISSN 1000-1239 CN 11-1777/TP

Journal of Computer Research and Development ›› 2016, Vol. 53 ›› Issue (4): 742-751.doi: 10.7544/issn1000-1239.2016.20151143

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A Caching Strategy for Internet Plus TV Based on Popularity Prediction

Zhu Chengang, Cheng Guang, Hu Yifei, Wang Yuxiang   

  1. (School of Computer Science and Engineering, Southeast University, Nanjing 211189) (Key Laboratory of Computer Network and Information Integration (Southeast University), Ministry of Education, Nanjing 211189)
  • Online:2016-04-01

Abstract: Internet plus TV tends to excessively consume storage space to achieve higher cache hit ratio. A novel cache schedule algorithm called PPRA(popularity prediction replication algorithm) is proposed in this paper based on programs popularity forecast. Firstly, according to statistical analysis from actual measurement, we apply random forests (RF) algorithm to construct a forecasting model of programs popularity. Subsequently, we use the principal component analysis (PCA) to overcome dimensionality curse and accelerate the forecasting process. Finally, we validate PPRA with authentic behavior data of a certain cable operator’s 1.3 million users in a period of 120 days. Our experimental results show that PPRA only consumes 30% storage space to achieve a fixed cache hit ratio compared with LRU and LFU algorithms, therefore the cost of Internet plus TV platform is saved.

Key words: Internet plus TV, popularity prediction, random forests (RF), caching strategy, dimensionality curse

CLC Number: