C-RAN carrier migration resource demand prediction method based on improved PSO

Abstract

The invention discloses a C-RAN carrier migration resource demand prediction method based on improved PSO. The method comprises the following steps: acquiring and preprocessing data, and generating a training sample set of a prediction model; determining the structure of a GRNN prediction model according to the generated training sample set; training the GRNN prediction model by using an improved PSO algorithm; and prediction the resource demand of a carrier virtual machine at a next moment by employing the trained GRNN prediction model. The problem in the existing carrier migration technology that resource allocation is carried out only depending on the load condition of the carrier virtual machine at the current moment, resulting in resource waste or resource shortage to cause short-term secondary migration is effectively solved; and in view of the defect that the existing prediction method cannot be applicable to the C-RAN scene with high instantaneity due to an overlong prediction time, the improved PSO algorithm is proposed to train the prediction model, so as to effectively improve the prediction accuracy and the prediction speed in resource demand prediction.

Description

technical field [0001] The invention belongs to the technical field of communication, and in particular relates to a C-RAN carrier migration resource requirement prediction method based on improved PSO. Background technique [0002] As people have higher and higher requirements for communication quality and communication forms, the traditional network architecture can no longer cope. In order to solve the shortcomings of the traditional network architecture, China Mobile proposed a new network architecture—C-RAN, which is based on centralized Green Wireless Access Network Architecture for Processing, Cooperative Radio and Real-Time Cloud Architecture. Its advantages are mainly reflected in the following aspects: 1. Lower network power consumption; 2. Lower capital expenditure and operation and maintenance costs of operators; 3. Dynamic sharing of baseband processing resources is realized through carrier migration technology, which improves resource utilization. utilization ...

AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to provide a C-RAN carrier relocation resource demand prediction method based on improved PSO, aiming to solve the problem of resource allocation in the current carrier relocation technology only according to the current load situation, which leads to waste of resources or short time caused by insufficient resources. The problem of secondary migration

And aiming at the shortcoming that the existing prediction method cannot be applied to the high real-time requirement scene of C-RAN due to the long prediction time, the present invention proposes an improved PSO algorithm based on the interval estimation of the excellent solution distribution to carry out the prediction model training

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