Adaptive Congestion Control Device for Dynamic Flow Optimization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing network congestion control methods provide a one-size-fits-all solution, leading to varying content delivery performance due to the lack of customization based on specific flow parameters, such as content type, receiving device characteristics, and network link conditions.
Innovation Solution
An adaptive congestion control device (ACCD) dynamically selects and customizes congestion control algorithms, such as BIC, CUBIC, and BBR, based on flow parameters to optimize content delivery performance by adjusting parameters like initial window sizes and response to congestion, ensuring optimal performance for each active flow.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a one-size-fits-all congestion control algorithm is used for all flows, then the device complexity is reduced and ease of operation is improved, but the content delivery performance varies widely and reliability deteriorates
Solution Approach 1:
The patent applies local quality by customizing congestion control algorithms specifically for video traffic flows. The system identifies video flows and applies tailored congestion control parameters (such as adjusted window sizes and sending rates) specifically to these flows, rather than applying uniform control to all traffic. This localized optimization improves video delivery reliability while maintaining simpler control for other traffic types.
Solution Approach 2:
The patent implements dynamics by continuously monitoring network conditions and dynamically adjusting congestion control parameters for video flows. The system adapts sending rates, window sizes, and other parameters in real-time based on current network congestion levels, packet loss rates, and flow characteristics. This dynamic adjustment maintains high reliability under varying network conditions while keeping the overall system manageable through automated control.
2Reliability
If congestion control is customized for different flows based on flow parameters, then content delivery performance and reliability are improved, but the device complexity increases
Solution Approach 1:
The patent applies segmentation by dividing congestion control into separate handling mechanisms for different traffic types. The system segments video flows from other traffic flows and applies specialized congestion control only to video traffic. This segmentation allows complex optimization for video while keeping overall system complexity manageable by not applying the same complexity to all traffic types.
Solution Approach 2:
The patent implements self-service through automated flow identification and congestion control selection. The system automatically detects video flows based on traffic patterns and characteristics, then autonomously applies appropriate congestion control algorithms without requiring manual configuration. This self-service approach handles the complexity internally while presenting a simplified interface for operation.
3Adaptability or versatility
If dynamic adjustment of congestion control parameters is implemented, then adaptability to different network conditions is improved and content delivery performance increases, but the complexity of control increases
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting specific congestion control parameters such as window sizes, sending rates, and timeout values based on network conditions and flow characteristics. The system modifies these parameters in response to measured network performance metrics, enabling adaptation to varying network conditions while maintaining a relatively simple base algorithm structure.
Solution Approach 2:
The patent implements feedback mechanisms by continuously monitoring network performance metrics (packet loss, latency, throughput) and using this information to adjust congestion control parameters. The system incorporates feedback loops that measure actual flow performance and automatically tune congestion control behavior accordingly, achieving high adaptability through automated closed-loop control rather than complex open-loop algorithms.
Data Source
AI summary
An adaptive congestion control device (“ACCD”) may dynamically optimize network congestion control for different active flows. The ACCD may initiate a first flow that is associated with a first set of flow parameters, may select a first congestion control algorithm from a plurality of congestion control algorithms based on the first set of parameters, and may control transmission of packets for the first flow according to the first congestion control algorithm. While the first flow is active, the ACCD may initiate a second flow that is associated with a different second set of flow parameters, may select a different second congestion control algorithm from the plurality of available congestion control algorithms based on the second set of parameters, and may control transmission of packets for the second flow according to the second congestion control algorithm.