Virtual network function resource consumption prediction method based on flow feature extraction

A technology for virtual network functions and traffic characteristics, applied in the field of virtual network function resource consumption prediction, can solve problems such as lack of capture, and achieve the effect of improving prediction accuracy and better effect

Active Publication Date: 2022-02-18
CHONGQING UNIV OF POSTS & TELECOMM
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  • Abstract
  • Description
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AI Technical Summary

Problems solved by technology

Although the model can capture rich relational semantics and details of the network structure, it is still lacking in capturing each node and meta-path

Method used

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  • Virtual network function resource consumption prediction method based on flow feature extraction
  • Virtual network function resource consumption prediction method based on flow feature extraction
  • Virtual network function resource consumption prediction method based on flow feature extraction

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Embodiment Construction

[0059] Embodiments of the present invention are described below through specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific implementation modes, and various modifications or changes can be made to the details in this specification based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the diagrams provided in the following embodiments are only schematically illustrating the basic concept of the present invention, and the following embodiments and the features in the embodiments can be combined with each other in the case of no conflict.

[0060] see Figure 1 to Figure 9 , the present invention proposes a VNF resource consumption prediction method (VNF-RPHIN) based on traffic feature extractio...

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Abstract

The invention relates to a virtual network function resource consumption prediction method based on flow feature extraction, and belongs to the field of mobile communication. The method comprises the following steps: S1, establishing different meta-paths between flow features and a CPU of a VNF through correlation between the flow features so as to construct an HIN; S2, acquiring a feature representation of each flow feature by using an HIN2Vec model; and S3, measuring the importance of each feature by using an attention mechanism, allocating different weights to the features, and then inputting the features are input into the MLP model to predict the resource consumption of the VNF. The method has good performance, and is superior to a traditional machine learning model and a common deep learning model in the aspect of prediction precision.

Description

technical field [0001] The invention belongs to the field of mobile communication, and relates to a virtual network function resource consumption prediction method based on traffic feature extraction. Background technique [0002] The development trend of the network is to use artificial intelligence technology to control and operate the network, and software-defined network and network function virtualization technologies play a very important role in this process. In the future network era, there is a greater need for edge computing, cloud computing, and network collaboration to optimize resource utilization. In the 5G communication network, the 5G network service is closer to the needs of users, so as to provide users with personalized needs. Among them, representative network service capabilities of 5G networks include network slicing and edge computing. Network slicing is a key feature of the application of network function virtualization (NFV) in the 5G phase. Networ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04L41/044H04L41/14H04L41/147H04L41/16H04L41/40G06N3/04G06N7/00G06N20/00G06N20/10
CPCH04L41/145H04L41/147H04L41/044G06N20/00G06N20/10G06N3/047G06N7/01G06N3/045Y02D10/00
Inventor 苏畅谭娅谢显中
Owner CHONGQING UNIV OF POSTS & TELECOMM
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