Network Twin Updating With Simulated Data to Cut Reporting Load
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Solution Overview
Problem
Frequent data collection and full data reporting in network management systems consume a large quantity of transmission resources due to the increased frequency of network data exchange between network management service consumer and provider entities, leading to higher resource consumption.
Innovation Solution
A network management method that involves generating a simulation network dataset using a data generation model trained on collected network data, allowing the creation or update of a network twin without frequent data retrieval from the provider entity, thereby reducing data transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the frequency of exchanging network data between network management service consumer entity and provider entity is increased to improve consistency between network twin and physical network, then the consistency accuracy is improved, but the transmission resource consumption increases
Solution Approach 1:
The patent uses a data generation model to create a simulation network dataset that copies and replicates the characteristics of the physical network data. This simulation dataset can be used to update the network twin without requiring frequent actual data exchanges with the physical network, thus maintaining consistency accuracy while reducing transmission resource consumption.
Solution Approach 2:
The patent pre-trains a data generation model using historical network data to generate simulation datasets in advance. This preliminary action allows the network management service consumer entity to update the network twin using pre-generated simulation data rather than frequently querying the physical network, reducing real-time transmission requirements.
2Measurement precision
If full data reporting is implemented to maintain network twin accuracy, then the measurement precision is improved, but the quantity of transmitted data increases
Solution Approach 1:
The data generation model creates a simulation network dataset that replicates the statistical characteristics and key features of the physical network data. This copied simulation data maintains the necessary accuracy for network twin updates without requiring the full volume of actual network data to be transmitted, thus reducing the quantity of transmitted data while preserving measurement precision.
Solution Approach 2:
The patent transforms the data from the physical network into a simulation dataset with adjusted parameters that capture the essential characteristics needed for network twin accuracy. By changing the data representation to a simulated form with equivalent statistical properties, the system maintains accuracy while reducing data volume requirements.
Data Source
AI summary
This application discloses a network management method, apparatus, and system, and a storage medium. A network management service consumer entity generates a first simulation network dataset based on a data generation model, where the data generation model is obtained through training based on a first network dataset, and the first network dataset includes network data collected from a physical network. In addition, the network management service consumer entity creates or updates a network twin based on the first simulation network dataset, where the network twin is a digital representation of the physical network for emulating the physical network. According to the solution of this application, the network twin is created or updated by using the simulation network dataset generated based on the data generation model. This reduces network data transmission of the physical network, thereby reducing consumption of transmission resources.