Selective Acknowledgment Tracking for Network Buffer Optimization
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Solution Overview
Problem
Current network devices face challenges in efficiently managing network traffic congestion and optimizing buffer utilization due to hardware limitations and the need for static configuration, leading to increased latency and obsolescence as they struggle to adapt to diverse and changing network conditions.
Innovation Solution
The implementation of Selective Tracking of Acknowledgments (STACKing) in network devices, which involves tracking and regenerating acknowledgments in main memory instead of interface buffers, combined with machine learning techniques to optimize traffic shaping based on traffic classes and congestion states, allowing for adaptive management of network traffic.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If network devices use static configuration and hardware-based buffer management, then device complexity is reduced, but adaptability to diverse and changing network conditions deteriorates
Solution Approach 1:
The patent implements dynamic buffer management where the network device continuously monitors network traffic patterns, congestion states, and buffer utilization metrics, then adapts buffer allocation and traffic shaping parameters in real-time. This allows the system to transition from static configuration to dynamic adaptation, resolving the contradiction between simplicity and adaptability.
Solution Approach 2:
The system changes operational parameters such as buffer sizes, traffic shaping rates, and acknowledgment tracking thresholds based on observed network conditions. By dynamically adjusting these parameters rather than relying on fixed hardware configurations, the device achieves adaptability while maintaining manageable complexity through software-based control.
2Quantity of substance
If network devices track all acknowledgments in interface buffers, then buffer utilization is maximized, but latency increases due to hardware limitations
Solution Approach 1:
The patent extracts the acknowledgment tracking function from the hardware interface buffer and implements it in software memory. This separation allows the interface buffer to be used more efficiently for actual data transmission while acknowledgment tracking occurs in software, reducing the time acknowledgments spend in buffer and thereby reducing latency while maintaining effective buffer utilization.
Solution Approach 2:
The system introduces software-based acknowledgment tracking as an intermediary layer between the network interface and the buffer management system. This intermediary handles acknowledgment processing in software, allowing hardware buffers to operate more efficiently and reducing the time acknowledgments block buffer resources, thus reducing latency.
3Productivity
If network devices use hardware-based traffic shaping, then traffic management is more efficient, but adaptability to diverse traffic classes deteriorates
Solution Approach 1:
The patent implements dynamic traffic shaping that adapts to diverse traffic classes by continuously monitoring traffic patterns, application types, and network conditions. The system dynamically adjusts shaping parameters for different traffic classes rather than using fixed hardware rules, achieving both efficiency and adaptability through software-based dynamic control.
Solution Approach 2:
The system creates a universal traffic shaping mechanism that can handle multiple traffic classes and protocols through software-based classification and shaping rules. This multi-functional approach allows a single flexible system to replace multiple specialized hardware configurations, achieving adaptability to diverse traffic types while maintaining efficient traffic management.
Data Source
AI summary
Systems and methods provide for Selective Tracking of Acknowledgments (STACKing) to improve buffer utilization and traffic shaping for one or more network devices. A network device can identify a first flow that corresponds to a predetermined traffic class and a predetermined congestion state. The device can determine a current window size and congestion threshold of the first flow. In response to a determination to selectively track a portion of acknowledgments of the first flow, the device can track, in main memory, information of a first portion of acknowledgments of the first flow. The device can exclude, from one or more buffers, a second portion of acknowledgments of the first flow. The device can re-generate and transmit segments corresponding to the second portion of acknowledgments at a target transmission rate based on traffic shaping policies for the predetermined traffic class and congestion state.