Traffic Management Using Real-Time QoE Feedback
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Solution Overview
Problem
Conventional traffic management systems often lower Quality of Experience (QoE) for users by restricting bandwidth, even in the absence of congestion, and may not adequately address underlying congestion issues due to insufficient enforcement policies.
Innovation Solution
A system and method that utilize a QoE measurement module to monitor network traffic in real-time, a control module to analyze and determine traffic management actions based on QoE metrics, and a traffic management module to apply these actions, including shaping traffic flow, reprioritizing traffic, and packet marking, using adaptive control techniques like fuzzy logic to dynamically adjust traffic management strategies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional traffic management systems limit bandwidth for predetermined traffic types or during peak hours, then congestion is avoided, but Quality of Experience (QoE) is lowered by affecting subscribers even in the absence of actual congestion
Solution Approach 1:
The system implements a feedback mechanism where QoE metrics are continuously monitored and fed back to the traffic management module. The controller receives QoE measurements, analyzes them, and dynamically adjusts traffic management actions based on the feedback loop. This ensures that bandwidth restrictions are applied only when actually needed to maintain QoE, rather than using static predetermined rules that unnecessarily degrade user experience.
Solution Approach 2:
The traffic management system transitions from static, predetermined bandwidth limitations to dynamic, real-time adjustments based on actual network conditions and QoE measurements. The controller continuously adapts traffic management actions by analyzing current QoE metrics and adjusting enforcement policies dynamically, allowing the system to respond to actual congestion rather than applying fixed restrictions.
2Productivity
If conventional traffic management systems apply predetermined enforcement policies, then some congestion control is achieved, but the sum of enforcement policies is insufficient to relieve actual congestion
Solution Approach 1:
The system uses feedback from real-time QoE measurements to continuously evaluate and adjust the sufficiency of enforcement policies. The controller analyzes QoE trends and determines whether current traffic management actions are adequate, increasing enforcement when QoE degradation is detected and reducing it when QoE is satisfactory, ensuring policies are always sufficient to relieve actual congestion.
Solution Approach 2:
The traffic management system performs self-adjustment by automatically analyzing its own performance through QoE metrics and modifying its enforcement policies accordingly. The controller monitors the effectiveness of current policies and autonomously adjusts traffic management actions to ensure adequate congestion relief without requiring external intervention or fixed predetermined rules.
Data Source
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AI summary
The present disclosure provides a system and a method for managing network traffic. The traffic management system has a quality of experience (QoE) measurement module configured to monitor a QoE metric in real-time. A control module is configured to periodically receive the QoE metric and determine a traffic management action based on the QoE metric. A traffic management module is configured to apply the traffic management action to the network traffic.