Adaptive Congestion Management for Edge Network Segments
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Solution Overview
Problem
Existing congestion management techniques for broadband data services are ineffective in dynamically adjusting bandwidth allocation to address increasing customer demand, leading to network congestion and customer dissatisfaction, as they rely on fixed rate reductions and do not accurately measure congestion states.
Innovation Solution
Adaptive congestion management systems that gather periodic usage measurements of edge network segments and customers to dynamically adjust transfer rates, applying restrictions only when congestion occurs and removing them when congestion subsides, using Exponentially Weighted Moving Average calculations and profile-based rate adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If fixed rate reduction techniques are applied to manage congestion, then network congestion is reduced, but customer satisfaction deteriorates due to unnecessary rate limitations
Solution Approach 1:
The patent implements dynamic rate adjustment by continuously monitoring congestion metrics and adapting transfer rates in real-time. Instead of fixed rate reductions, the system dynamically modifies rates based on current network conditions, customer usage patterns, and congestion severity, allowing optimal balance between network throughput and customer service quality
Solution Approach 2:
The system employs feedback mechanisms by monitoring congestion metrics, customer usage patterns, and network performance continuously. This feedback loop enables the system to detect when congestion occurs, apply appropriate rate adjustments, and remove restrictions when congestion clears, ensuring rate limitations are applied only when necessary rather than fixed reductions
2Productivity
If maximum allowed rates are enforced for digital traffic types, then congestion is managed, but measurement precision deteriorates due to lack of direct congestion state monitoring
Solution Approach 1:
The patent replaces traditional mechanical congestion management (fixed rate enforcement based on traffic type) with an intelligent system that uses machine learning algorithms and analytics to detect congestion states. This substitution enables precise measurement of actual congestion conditions through multiple metrics including queue depth, packet loss rates, and latency measurements, rather than relying on simplified traffic-type-based assumptions
3Productivity
If active management techniques reduce permitted bandwidth for high-usage customers, then overall network capacity is improved, but device complexity increases due to continuous monitoring and adjustment requirements
Solution Approach 1:
The patent implements self-service mechanisms where the congestion management system automatically monitors network conditions, identifies congestion states, applies rate adjustments, and removes restrictions without manual intervention. The system uses automated algorithms to analyze usage patterns, detect congestion, and execute rate modifications, reducing the need for complex manual management while maintaining high network capacity utilization
Data Source
AI summary
A system and method for adaptive congestion management uses measurements of usage of each edge network segment both per-customer and for each edge network segment as a whole. The technique then processes these measurements to determine what changes to make to allowed transfer rates to alleviate congestion. Adaptive congestion management also uses these measurements to determine when to remove any restrictions on transfer rates in the case that the edge network segment is no longer congested.