An optimal path selection algorithm based on machine learning under SDN

Abstract

An optimal path selection algorithm based on machine learning under SDN, build an SDN platform, simulate the real network environment, collect discrete real-time network status data, classify the different requirements of QoS indicators according to different services in network transmission, and organize experiments Data, get the sample data set, use the heuristic algorithm to filter the sample data set according to the consideration standards of different businesses for each indicator, and label the optimal path corresponding to each set of data, and finally use the machine learning algorithm to train the data Set to obtain a classifier to achieve the purpose of fast dynamic routing. The result of the present invention is basically the same as the optimization result of the heuristic algorithm, and the calculation time of the model is much shorter than that of the heuristic algorithm, thereby satisfying the necessary condition for fast decision-making in actual network operation. Compared with the particle swarm algorithm, the extreme learning machine algorithm of the present invention greatly shortens the cpu running time required for calculation, and can fully meet the requirements of real network deployment.

Description

technical field [0001] The present invention relates to the problem that the general routing method under the software-defined network architecture will generate relatively high time cost, and proposes a low-time-consuming multi-constraint QoS routing planning method, specifically relating to a machine-learning-based optimal routing method under SDN optimal path selection algorithm. Background technique [0002] According to the 42nd "Statistical Report on Internet Development in China" released by the China Internet Network Information Center, as of June 2018, the number of Internet users in my country has reached 802 million, and the number of mobile users has reached 788 million. And with the rapid development of information technology and the continuous emergence of emerging technologies such as cloud computing and big data, network data has shown explosive growth in terms of both scale and type. Ubiquitous network access and large bandwidth make the dynamic management ...

AI Technical Summary

Problems solved by technology

[0003] The purpose of the present invention is to significantly reduce the time consumption of the algorithm in order to meet the different requirements of multiple QoS indicators in different services, solve the problem of introducing high time cost in the existing algorithm, and propose a machine learning-based optimal solution under SDN. The optimal path selection algorithm can solve the fast dynamic routing of different business flows

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