Network Optimization Policy for Dynamic Service Flow Requirements
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Solution Overview
Problem
The efficiency of manually configuring network optimization policies in wide area networks is low, and existing methods fail to adapt to dynamic changes in network performance, leading to suboptimal transmission performance of service flows.
Innovation Solution
A network optimization device uses an algorithm to automatically determine a network optimization policy based on performance parameters and service requirements, selecting appropriate technologies and parameters to ensure transmission performance meets service demands, even in dynamically changing networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual configuration of network optimization policies by operation and maintenance engineers is used, then the policies can be customized based on service requirements, but the efficiency of determining and configuring policies is low
Solution Approach 1:
The network optimization device automatically collects network performance parameters, analyzes service requirements, and determines optimization policies without human intervention. The device serves itself by implementing the complete workflow from data collection to policy generation and execution, eliminating the need for manual configuration by operation and maintenance engineers.
Solution Approach 2:
The patent replaces the manual mechanical process of policy configuration with an automated algorithmic system. The network optimization algorithm automatically processes network performance data and service requirements to generate optimization policies, substituting human engineering work with computational automation.
2Adaptability or versatility
If network optimization policies are manually configured based on service requirements, then policies can satisfy specific service demands, but they do not adapt well to dynamic changes in network performance
Solution Approach 1:
The network optimization device continuously collects network performance parameters and uses this feedback to dynamically adjust optimization policies. The system monitors network conditions in real-time and automatically updates policies based on current performance data, enabling adaptation to changing network conditions without manual reconfiguration.
Solution Approach 2:
The patent transforms static manual policy configuration into a dynamic automated system. The network optimization algorithm continuously processes updated network performance parameters and adjusts policies in real-time, making the system adaptable to dynamic network conditions rather than relying on fixed manually-configured policies.
3Measurement precision
If comprehensive network performance parameters are collected for all links, then accuracy of policy determination is improved, but data processing volume and complexity increase
Solution Approach 1:
The network optimization device extracts only the necessary performance parameters from the network links that are relevant to the target service flow. Instead of collecting and processing all possible network data, the system identifies and processes only the critical parameters needed for accurate policy determination, reducing data volume while maintaining accuracy.
Solution Approach 2:
The patent applies local quality by focusing data collection and processing on specific network links that are directly relevant to the target service flow. The system processes performance parameters locally for only those links that impact the service flow, rather than uniformly processing data from the entire network, thereby reducing overall processing complexity.
Data Source
AI summary
A method for determining a network optimization policy, an apparatus, and a system are provided. A network optimization device can process a performance parameter of a network and a service requirement of a target service flow by using a network optimization algorithm, to obtain a target network optimization policy, and can apply the target network optimization policy to the target service flow, to enable transmission performance of the target service flow to satisfy the service requirement. Because the network optimization device can automatically determine the network optimization policy based on the network optimization algorithm, efficiency of determining the network optimization policy is effectively improved. In addition, when determining the network optimization policy, the network optimization device further considers the performance parameter of the network.