High-performance interface flow distribution method supporting intelligent scheduling
By analyzing network infrastructure and traffic patterns, constructing traffic models, and utilizing intelligent algorithms to generate strategies, the problem of long response times for interface traffic allocation was solved, thereby improving network service quality and response speed.
CN120935120APending Publication Date: 2025-11-11CHINA NAT BUILDING MATERIALS TECH CO LTD +2
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Patent Information
- Application Number
- CN202410718309.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-06-04
- Publication Date
- 2025-11-11
AI Technical Summary
Technical Problem
Existing interface traffic allocation methods have long response times, leading to a decline in service quality and making it difficult to efficiently cope with high-concurrency, high-traffic network scenarios.
Method used
By analyzing the status of network infrastructure, continuously monitoring and collecting indicator data, identifying traffic patterns and trends, constructing network traffic models, using intelligent algorithms to generate and simulate traffic allocation strategies, and dynamically adjusting traffic paths and priorities.
Benefits of technology
It enables the prediction and intelligent allocation of traffic trends, improving system response speed and overall service quality, and ensuring that critical businesses receive sufficient bandwidth resources.
✦ Generated by Eureka AI based on patent content.
Abstract
The invention relates to the technical field of intelligent scheduling, in particular to a high-performance interface flow distribution method supporting intelligent scheduling. The method comprises the following steps: S1, analyzing the infrastructure condition of a current network, and determining the performance limit of network equipment according to historical fault records; s2, continuously monitoring and collecting indexes of a network interface, analyzing historical data, identifying a traffic mode and predicting a future trend of the traffic; s3, constructing a network flow model based on the collected index data, and simulating network behaviors and performance expressions under different distribution strategies; and S4, generating a flow distribution strategy by using an intelligent algorithm, performing a simulation test of the strategy in a simulation environment, and evaluating the effect of the strategy. According to the method, the flow path and the priority can be dynamically adjusted through a strategy for carrying out future trend prediction on the flow and generating an intelligent algorithm, it is ensured that key services and real-time applications obtain enough bandwidth resources, and therefore the system response speed and the overall service quality are improved.
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