Dual Virtual Queue AQM for Low-Latency ECN Traffic
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Solution Overview
Problem
Existing congestion control and active queue management algorithms in communication networks struggle to support a wide range of requirements, including compatibility with ECN-capable protocols like DCTCP, varying delay requirements, fairness among flows, refined resource sharing policies, and general compatibility among different congestion control algorithms.
Innovation Solution
Implement a dual queue system with physical and virtual queues, where data packets are stored based on delay characteristics and marked with ECN indicators using congestion threshold values determined from virtual queues, allowing for strict priority scheduling and compatibility with multiple congestion control algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If packets are marked with ECN indicators and congestion threshold values are used for selective marking, then compatibility with ECN-capable protocols like DCTCP is improved, but device complexity increases due to the need for dual queue management and virtual queue simulations
Solution Approach 1:
The patent creates virtual copies of physical queues (virtual queues) that simulate congestion conditions without requiring actual packet buffering. These virtual queues are lightweight data structures that mirror the behavior of physical queues, allowing the system to apply ECN marking based on simulated congestion thresholds while maintaining simplicity in the actual packet handling path.
Solution Approach 2:
The virtual queues act as an intermediary layer between the physical queues and the ECN marking logic. Instead of directly managing complex congestion control algorithms in the packet forwarding path, the system uses virtual queues to mediate congestion detection and threshold comparison, simplifying the actual packet processing while maintaining algorithm compatibility.
2Loss of time
If strict priority scheduling is implemented for low latency traffic, then delay requirements are met, but bandwidth sharing control among different traffic types becomes difficult
Solution Approach 1:
The patent segments the queueing system into multiple physical queues (e.g., low-latency queue and best-effort queue) that are served in strict priority order. This segmentation ensures that time-sensitive traffic receives preferential treatment and experiences minimal queuing latency, while less time-sensitive traffic is handled in subsequent priority levels.
Solution Approach 2:
The system dynamically adjusts congestion threshold values for different physical queues based on their delay requirements and traffic characteristics. By changing the threshold parameters adaptively, the system can control bandwidth sharing among different traffic types while maintaining strict priority scheduling, allowing low-latency traffic to occupy bandwidth up to its threshold before affecting other queues.
3Reliability
If multiple physical queues are used to handle different delay requirements, then service quality is improved, but processing overhead and device complexity increase
Solution Approach 1:
The patent merges the management of multiple physical queues with a unified virtual queue system. Instead of independently managing each physical queue's congestion control, the system combines their states into virtual queues that share common ECN marking logic and threshold management. This reduces processing overhead by consolidating redundant operations while maintaining the benefits of multiple queues for different service qualities.
4Measurement precision
If congestion threshold values are dynamically determined from virtual queues, then resource sharing precision is improved, but measurement and calculation complexity increases
Solution Approach 1:
The virtual queues automatically determine their own congestion threshold values based on their current state and configuration parameters. Each virtual queue monitors its own length and dynamically adjusts the ECN marking threshold without requiring external control or complex centralized calculations. This self-service approach simplifies the overall system while maintaining precise resource sharing control.
Data Source
AI summary
A method for handling data packets by a communication node in a communication network, the method comprising storing received data packets in at least two physical queues, wherein a first of said at least two physical queues is associated with low latency data packets and a second of said at least two physical queues is associated with high latency data packets, wherein each data packet is stored in one of the at least two physical queues based on a delay characteristic associated with the data packet, for each received data packet, storing an associated information record in at least two virtual queues, VQs, wherein associated information for data packets stored in said high latency physical queue is stored in a second of said at least two virtual queues and wherein associated information for data packets stored in said low latency physical queue is stored in both said first and second of said at least two virtual queues, serving data packets from the at least two physical queues, using at least two Congestion Threshold Values, CTVs, wherein a first of said at least two CTVs is applicable to data packets in said low latency physical queue and wherein both said first and second of said at least two CTVs are applicable to data packets in said low latency physical queue and data packets in said high latency physical queue, wherein said at least two CTVs are used for at least one of dropping and marking packets based on their associated information.