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SYSTEM AND METHODS FOR INTELLIGENT SERVICE FUNCTION PLACEMENT AND AUTOSCALE BASED ON MACHINE LEARNING

机译:基于机器学习的智能服务功能展示位置和自动尺度的系统和方法

摘要

A method implemented by a computing device to optimize resource usage of service function chains (SFCs) in a network using machine learning. The method includes obtaining, from an autoscale machine learning (ML) system associated with a virtual network function (vNF), a suggested adjustment to an amount of resources provisioned for the vNF. The autoscale ML system is trained online using machine learning to predict an amount of resources to be utilized by the vNF. The autoscale ML system is configured to receive as input an amount of resources currently utilized by the vNF and an amount of resources currently available to the vNF, determine using machine learning the suggested adjustment to the amount of resources provisioned for the vNF based on the input, and output the suggested adjustment. The method further includes providing the suggested adjustment to a resource re-allocator component.
机译:由计算设备实现的方法,以优化使用机器学习在网络中的服务功能链(SFC)的资源使用。 该方法包括从与虚拟网络功能(VNF)相关联的自动尺度机器学习(ML)系统获得,建议调整为VNF提供的资源量。 自动缩放ML系统在线使用机器学习培训以预测VNF的资源量。 自动尺寸ML系统被配置为接收VNF当前使用的资源量和当前用于VNF的资源量,确定使用机器学习建议的调整基于输入为VNF提供的资源量。 ,并输出建议的调整。 该方法还包括向资源重新分配器组件提供建议的调整。

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