Dynamic Network Traffic Scheduling via Detection Nodes
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing network traffic scheduling systems rely on static strategies based on DNS mapping tables, which are costly to maintain, inflexible, and require experienced personnel, limiting the ability to direct users to the best available server nodes and leading to suboptimal performance.
Innovation Solution
A dynamic scheduling and allocation system that uses a widespread detection network to gather performance data, filter, and group server nodes based on response time and resource utilization, allowing for automatic adjustments and simplifying configuration, eliminating the need for complex tables and experienced maintenance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If static DNS mapping tables are used for traffic scheduling, then traffic allocation can be achieved, but maintenance costs increase and timeliness deteriorates
Solution Approach 1:
The system enables automatic detection and dynamic grouping of server nodes through detection nodes that autonomously monitor performance metrics. The coverage table is automatically updated based on detected performance information, eliminating the need for manual maintenance by technicians while maintaining accurate traffic scheduling.
Solution Approach 2:
The patent transitions from static DNS mapping tables to dynamic server node grouping based on real-time performance detection. Server nodes are automatically reorganized into different coverage tables according to their detected performance metrics, allowing the system to adapt to changing conditions without manual intervention.
2Ease of operation
If static regional strategies are implemented, then traffic can be directed to different nodes, but flexibility deteriorates and optimal node selection is limited
Solution Approach 1:
The system creates different coverage tables for different detection nodes based on their specific performance characteristics and network conditions. Each detection node has a customized coverage table that reflects local performance quality, allowing flexible and optimized node selection for each specific context rather than applying uniform regional strategies.
3Measurement precision
If accurate strategies are constructed through long-term optimization, then traffic scheduling accuracy improves, but operation and maintenance costs increase
Solution Approach 1:
The system implements continuous performance detection where detection nodes monitor server node metrics and feed this information back to automatically update coverage tables. This feedback mechanism maintains high scheduling accuracy by continuously adapting to current performance conditions without requiring manual long-term optimization efforts.
Solution Approach 2:
The automatic detection and update system performs the optimization work autonomously based on detected performance information, eliminating the need for experienced technicians to continuously optimize strategies manually while maintaining high scheduling accuracy.
Data Source
Figure 1
Figure 2
Figure 3~4
AI summary
A method and system for dynamic scheduling and allocation of network traffic are provided. The method includes: distributing, by a central scheduling system, a domain name initial configuration table and a determination strategy to each detection node; detecting, by each detection node, each server node of a pre-set domain name in the domain name initial configuration table, thereby obtaining performance information of each server node; generating, by each detection node, a corresponding best coverage record; and converting, by the central scheduling system, the best coverage record into a target server node and feeding back, by the central scheduling system, the target server node to a local DNS server. The disclosed method and system for dynamic scheduling and allocation of network traffic improves network access speed and reduces operation and maintenance cost.