A double-strategy adaptive cache replacement method based on popularity prediction

Abstract

The application discloses a kind of double strategy adaptive cache replacement method based on popularity prediction, comprising: collecting equipment request data;With time slot as unit statistics content popularity and constructs model dataset;Build content popularity prediction model based on sequence model Seq2Seq, carry out model training and the structure and weight of the trained popularity prediction model are saved to file respectively.The double strategy adaptive cache replacement method based on popularity prediction provided by the application is for the scene of industrial edge node cache, for the characteristics that data popularity changes with time, excavates the heat trend and tidal nature law of data, and proposes double strategy adaptive cache replacement algorithm and method based on Seq2Seq in combination with traditional cache replacement algorithm and deep learning method.When the prediction model encounters the request sequence of unvisited access popularity, the adaptability of the method successfully improves the cache hit rate of system, reduces network delay, and guarantees the real-time service performance of industrial edge network.

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