Network Device QoS Configuration via Traffic Pattern Analysis
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Solution Overview
Problem
Current bandwidth allocation policies in network devices, such as routers and switches, require complex and esoteric parameter settings by operators, making it difficult for non-experts to configure Quality of Service (QoS) parameters effectively, especially for ensuring latency and packet drop rates for different traffic classes.
Innovation Solution
A network device with logic to receive user preference information for QoS, measure traffic patterns, and generate a configuration template based on these preferences to prioritize data transmission according to defined bandwidth allocation policies, allowing for automatic configuration of QoS parameters using intuitive parameters like latency and packet drop rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If bandwidth allocation policies are configured using detailed CoS attributes, buffer parameters, and scheduler configurations, then QoS performance is improved, but operator complexity and difficulty of configuration increase
Solution Approach 1:
The patent introduces an intermediary component that automatically generates configuration templates based on high-level QoS requirements. This intermediary translates user-friendly parameters (latency, packet drop rates) into detailed technical configurations (CoS attributes, buffer parameters, scheduler configurations), thereby resolving the contradiction between QoS performance and configuration ease.
Solution Approach 2:
The system performs self-service by automatically generating and updating configuration templates based on monitored traffic patterns and measured QoS performance. The network device autonomously adjusts buffer parameters, scheduler configurations, and CoS attributes without requiring manual operator intervention, thus improving QoS while eliminating configuration complexity.
2Measurement precision
If manual fine-tuning of QoS parameters is performed, then precise QoS control is achieved, but time and expertise requirements increase
Solution Approach 1:
The patent implements a feedback mechanism where the network device continuously monitors actual QoS performance metrics (latency, packet drop rates) and compares them against target values. Based on this feedback, the system automatically adjusts configuration parameters and updates templates, achieving precise QoS control without manual fine-tuning and eliminating the time and expertise burden.
Solution Approach 2:
The system performs preliminary action by pre-generating configuration templates with appropriate QoS parameters based on traffic patterns and requirements. These pre-configured templates are ready for deployment without requiring manual fine-tuning, thus achieving precise QoS control while significantly reducing configuration time and expertise requirements.
3Manufacturing precision
If configuration templates are manually created and updated, then configuration accuracy is maintained, but adaptability to changing traffic patterns decreases
Solution Approach 1:
The patent transforms static manual configuration templates into dynamic, adaptive templates that automatically adjust to changing traffic patterns. The system continuously monitors traffic characteristics and QoS performance, then dynamically updates configuration parameters and templates accordingly. This maintains configuration accuracy through automated validation while providing adaptability to evolving network conditions.
Solution Approach 2:
Through continuous feedback monitoring of traffic patterns and QoS metrics, the system automatically detects changes in network conditions and adjusts configuration templates in real-time. This feedback-driven approach maintains configuration accuracy by validating changes against QoS requirements while providing continuous adaptability to changing traffic patterns without manual intervention.
Data Source
AI summary
A network device implements automatic configuration of Quality of Service (QoS) parameters in response to operator specification of a relatively few and easily understandable “high level” parameters such as, for example, latency requirements or an acceptable rate of packet drops. In one implementation, a network device may receive user preference information that relates to a Quality of Service (QoS) for network traffic passing through the network device and may measure traffic patterns through the network device. The device further generates a configuration template based on the measured traffic patterns and on the user preference information transmit the data in an order of transmission that is prioritized according to a bandwidth allocation policy defined by the configuration template.