Learning Popularity for Proactive Caching in Cellular Networks

Khai Nguyen Doan, Thang V. Van Nguyen, Tony Q.S. Quek

研究成果: Chapter

摘要

Video data have been showed to dominate a significant portion of mobile data traffic and have a strong influence on a backhaul congestion issue in cellular networks. To tackle the problem, proactive caching is considered as a prominent candidate in terms of cost efficiency. In this chapter, we study a novel popularity-predicting-based caching procedure that takes raw video data as input to determine an optimal cache placement policy, which deals with both published and unpublished videos. For dealing with unpublished videos whose statistical information is unknown, features from the video content are extracted and condensed into a high-dimensional vector. This type of vector is then mapped to a lower-dimensional space. This process not only alleviates the computational burden but also creates a new vector that is more meaningful and comprehensive. At this stage, different types of prediction models can be trained to anticipate the popularity, for which information from published videos is used as training data.

原文English
主出版物標題Wireless Edge Caching
主出版物子標題Modeling, Analysis, and Optimization
發行者Cambridge University Press
頁面127-145
頁數19
ISBN(電子)9781108691277
ISBN(列印)9781108480833
DOIs
出版狀態Published - 2021 1月 1

All Science Journal Classification (ASJC) codes

  • 一般工程
  • 一般電腦科學

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