Congestion Profiling for Proactive Network Device Control
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Solution Overview
Problem
Computer networks experience congestion, leading to transmission delays and data loss, which existing protocols like QCN address reactively rather than proactively.
Innovation Solution
Generating and updating congestion profiles for network switching devices based on congestion notification messages to proactively control data transmission rates and routes, mitigating congestion before it occurs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If reactive congestion control protocols like QCN are used, then congestion notification and reaction are achieved, but proactive congestion mitigation and prevention are not possible
Solution Approach 1:
The patent applies preliminary action by proactively adjusting transmission rates and selecting alternative routes before congestion occurs. The system uses historical congestion data and machine learning predictions to anticipate future congestion events and take preventive actions, thereby resolving the contradiction between reactive response and proactive mitigation.
Solution Approach 2:
The system dynamically adjusts transmission parameters based on real-time network conditions and predicted congestion patterns. By continuously updating transmission rates and route selections based on current network state and historical data, the system transitions from static reactive control to dynamic proactive control, improving both reliability and response time.
2Productivity
If data transmission rate is increased to improve productivity, then network throughput is improved, but congestion and data loss increase
Solution Approach 1:
The system performs preliminary actions by predicting future congestion events and pre-adjusting transmission rates to avoid exceeding capacity thresholds. This allows the system to maintain high throughput while preventing congestion before it occurs, rather than reacting after congestion has manifested.
Solution Approach 2:
The system implements feedback mechanisms that continuously monitor network conditions, historical congestion patterns, and transmission effectiveness. This feedback loops back into the transmission rate adjustment algorithm, enabling the system to learn from past congestion events and optimize future transmission decisions to balance throughput and congestion avoidance.
3Reliability
If congestion control is implemented to prevent data loss, then network reliability is improved, but transmission delay increases
Solution Approach 1:
By taking preliminary actions to adjust transmission rates before congestion occurs, the system prevents data loss while minimizing transmission delay. The proactive adjustment ensures that transmission capacity is optimized in advance, avoiding the need for reactive throttling that would cause significant delays.
Data Source
AI summary
A method may include transmitting data frames from a reaction point of a source device. The method may also include receiving, at the reaction point, congestion notification messages corresponding to the transmitted data frames and containing congestion feedback data regarding a particular network switching device and an identifier of the particular network switching device. The method may also include modifying a congestion profile for the particular network switching device by correlating the identifier of the particular network switching device to a profile entry, and updating the profile entry with the congestion feedback data.