Optimization method of vod service cache based on xgboost algorithm in edge network environment

Abstract

The invention discloses a VOD service cache optimization method based on an XGBoost algorithm in an edge network environment, comprising the following steps: collecting video data; taking the average visit volume as the prediction target, performing regression modeling with the XGBoost algorithm to obtain a prediction model; using the prediction model Predict the average access volume; establish a cache optimization model based on the prediction results; use the knapsack algorithm to solve the optimization model to obtain the final cache solution. The present invention considers that the edge server needs to process a large amount of video information, and the excellent data analysis ability of machine learning in big data processing, so that the edge server can minimize the service access delay, improve the cache efficiency of the edge server, and the The scheme is very simple and easy to implement, and has a good application prospect.

Description

technical field [0001] The invention belongs to the technical field of edge networks, and in particular relates to a VOD service cache optimization method based on an XGBoost algorithm in an edge network environment. Background technique [0002] With the development of science and technology, ports and devices of various standards, as well as various services and applications are connected to the Internet, resulting in explosive growth of business requests in the network, and then a blowout of data traffic in the network growth, mainly due to the growth of video traffic. The core network is an important part of business distribution and service provision. One of the main functions of the core network is to connect the requests entering the network through different standard equipment and interfaces to different service networks according to business requirements, so that each business request can get the due service. Another main function of the core network is to act as ...

AI Technical Summary

Problems solved by technology

The prediction of video services will directly affect the cache efficiency of the edge server. The cache hit rate is high, and the user obtains data on the edge side, and the delay will be reduced. Otherwise, the user will obtain data from the core network instead, and the delay will be greatly increased.

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