Dynamic Queue Size Adjustment for Data Routing Latency
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Solution Overview
Problem
Network routers face challenges in meeting service level agreements (SLAs) due to trapping of lower priority service frames in queues, leading to increased routing latency and potential SLA violations, especially during data congestion scenarios.
Innovation Solution
Implementing a queue optimization algorithm that dynamically alters the maximum queue size based on throughput parameters such as administrative and operational peak information rates and maximum burst sizes to prevent enqueuing of lower priority frames, thereby reducing routing latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the MBS parameter is set too high to enable burst traffic handling, then the ability to serve bursty traffic up to PIR is improved, but lower priority service frames become temporarily trapped in the queue causing transmission delays that violate SLA
Solution Approach 1:
The patent implements dynamic adjustment of the maximum queue size parameter based on real-time network conditions. The system monitors current traffic patterns and adjusts the MBS parameter dynamically rather than using a fixed high value, allowing the queue to adapt its size to prevent frame trapping while still accommodating burst traffic when appropriate
Solution Approach 2:
The system employs feedback mechanisms to monitor queue depth, frame waiting times, and traffic patterns. Based on this feedback, the maximum queue size parameter is adjusted in real-time to prevent lower priority frames from being trapped indefinitely, thus resolving the contradiction between handling bursts and preventing delays
2Loss of time
If the MBS parameter is set too low to prevent frame trapping, then transmission delays of lower priority frames are reduced, but the queue cannot accommodate burst traffic causing service frames to be dropped
Solution Approach 1:
The maximum queue size is adjusted dynamically based on current network conditions rather than being fixed at a low value. During burst periods, the queue size is temporarily increased to accommodate the traffic surge, while during normal periods it is reduced to prevent frame trapping, thus maintaining both low delays and high reliability
Solution Approach 2:
The system changes the MBS parameter value based on detected traffic patterns and network conditions. When bursts are detected, the parameter is increased to prevent drops; when traffic is stable, it is decreased to prevent trapping, resolving the contradiction between preventing drops and maintaining low latency
3Device complexity
If a fixed maximum queue size is used to simplify router configuration, then device complexity is reduced, but the router cannot adapt to varying traffic patterns causing either frame trapping or packet drops
Solution Approach 1:
The router automatically monitors its own queue conditions and adjusts the maximum queue size parameter without external intervention. The system self-adapts to varying traffic patterns by detecting bursts and frame trapping conditions, eliminating the need for complex manual configuration while maintaining high adaptability
Solution Approach 2:
The system uses feedback from queue depth monitoring and traffic pattern analysis to automatically adjust the MBS parameter. This closed-loop control enables the router to adapt to varying traffic conditions without requiring complex manual configuration, resolving the contradiction between simplicity and adaptability
Data Source
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AI summary
The dynamic proportioning of a maximum queue size of a data transport device queue based on throughput parameters may decrease routing latency of a data transport device. A maximum queue size parameter for a data queue may be calculated based on at least a plurality of throughput parameters during routing of data traffic from a data source device to a data recipient device. Subsequently, a maximum queue size of the data queue may be decreased according to the maximum queue size parameter to prevent enqueuing of incoming service frames into the data queue. The lack of enqueueing of the incoming service frames may cause the data source device to retransmit the one or more incoming service frames to the data transport device, instead of allowing the one or more incoming service frames to be enqueued and trapped in the data queue by additional incoming service frames.