Mobile network edge cooperation cache model construction method based on machine learning

Abstract

The invention discloses a mobile network edge cooperation cache model construction method based on machine learning. The method comprises the steps of 1, establishing a network training model according to content request data sent by a user; 2, enabling a judgement routing module in the network training model to carry out base station identification on content request data sent by a user accordingto an adaptive selection action requirement; step 3, enabling an updating module in the network training model to perform cache replacement on the local base station according to replacement action requirements; and 4, repeating the steps 1-3 until the network training model is stable, so that the user access time delay can be remarkably reduced, the cache hit rate is improved, and the backbone network flow pressure is relieved.

Description

technical field [0001] The invention relates to the field of mobile communication, in particular to a machine learning-based mobile network edge cooperative caching mechanism. Background technique [0002] With the rapid development of wireless access technology and mobile devices, Internet services and applications are gradually migrating to mobile networks. Mobile network traffic is experiencing explosive growth. Limited wireless spectrum resources and traditional mobile network architecture are difficult to cope with the explosive growth of mobile traffic. At the same time, mobile users' requirements for business service quality are constantly increasing. The study found that most of the traffic is used to download the same popular content, which brings great pressure and challenges to the mobile network. Repeated content transmission increases the pressure on the backhaul link, wastes network resources, and reduces user experience. Cache technology is widely used, from...

AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to provide a solution for edge cooperative caching in mobile networks. Based on the computing and storage capabilities of base stations at each level, a caching framework for layered cooperation and same-layer cooperation is formed to support large-scale and various types of intelligent terminals, and to learn Mechanisms to adapt to complex, dynamic and changeable user requests and network environments, and solve the content request routing and cache replacement problems of base stations at all levels, so as to improve users' online experience and reduce user access delays

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