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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

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Published on: September 8, 2023

A multi-queue-based ECN marking strategy for multi-class QoS guarantee in programmable networks.

Yazhi Liu¹, Xinyi Yao¹, Zhigang Yang²

¹College of Artificial Intelligence, North China University of Science and Technology, Tangshan, China.

Peerj. Computer Science

|December 9, 2024

Summary

This summary is machine-generated.

This study introduces a novel multi-queue Explicit Congestion Notification (ECN) marking strategy to meet diverse Quality of Service (QoS) demands from network applications. The new approach dynamically adjusts ECN marking thresholds and scheduling weights for improved performance and fairness.

Keywords:

P4 Programmable data plane QoS Queue scheduling Queuing theory

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Area of Science:

Computer Science
Network Engineering
Data Communications

Background:

Rapid growth in network applications creates varied Quality of Service (QoS) demands.
Existing Explicit Congestion Notification (ECN) marking methods lack support for diverse QoS requirements.

Purpose of the Study:

To introduce a multi-queue ECN marking strategy for enhanced QoS guarantees.
To address the limitations of current ECN methods in handling varied application needs.

Main Methods:

Utilized virtual queues and dynamic weighted round-robin scheduling for traffic partitioning in a programmable data plane.
Developed a multi-queue, multi-class QoS queuing model based on traffic requirements and network conditions.
Dynamically determined ECN marking thresholds and round-robin weights in real-time.

Main Results:

The proposed strategy demonstrated superior performance in queue length, Round Trip Time (RTT), and throughput compared to DCQCN, P4QCN, and TCN.
Achieved dynamic QoS adjustments for different network applications.
Ensured fairness among different traffic types.

Conclusions:

The multi-queue ECN marking strategy effectively meets dynamic QoS requirements for diverse network applications.
The approach offers significant advantages over existing methods in performance stability, feedback speed, and traffic fairness.