设计和开发一个基于意图的智能网络,使用机器学习提供QoS

Marco Vinicio Barzallo Huanga, Remigio Ismael Hurtado Ortiz, Juan Daniel Amay Marca
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引用次数: 0

摘要

对带宽的需求是目前公司使用互联网所需要的挑战,每天都可以看到大量的数据通过网络循环,如文件,电话,视频通话,在线购物或订阅流媒体服务,这产生了网络流量的瓶颈,因此这使得维护和管理变得困难,需要时间和人力。为了解决这个问题,建议使用差异化服务的架构来优先处理一种流量并获得服务质量(QoS),此外还将使用活动的自动化,即使用人工智能(AI)开发神经网络来识别模式并获得预测,机器学习(ML)将预测何时会发生改变网络资源的事件。为了证明该方法的有效性,使用了由已开发基础设施的数据生成的专有数据集,因此使用质量度量平均绝对误差(MAE)对方法进行了评估。最后,一个基于意图的网络(IBN)将被实施,因此本研究打算留下一个基础,以便所提议的系统可以得到改进,或者可以开发其他方法来实现数据中心的自动化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design and development of an intent-based intelligent network using machine learning for QoS provisioning
The demand for bandwidth is currently a challenge for the use of the Internet that companies require, it is common to see daily the exorbitant amount of data that circulate through the network as files, calls, video calls, online shopping or subscription streaming services, this generates a bottleneck in network traffic therefore this makes maintenance and management difficult requiring time and human effort. To solve this problem it is proposed to use the architecture of differentiated services to prioritize a type of traffic and obtain Quality of Service (QoS), in addition the automation of activities will be used, that is, with artificial intelligence (AI) a neural network is developed to identify patterns and obtain predictions, machine learning (ML) that will predict when there will be events that alter the resources in the network. To demonstrate the effectiveness of the method, a proprietary dataset generated with data from the developed infrastructure is used, therefore the methods are evaluated with the quality metric Mean Absolute Error (MAE). At the end an Intention Based Network (IBN) will have been implemented, therefore this research intends to leave a base so that the proposed system can be improved or other methods can be developed to automate data centers.
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