This presentation will focus on an innovative dynamic Explicit Congestion Notification (ECN) threshold testing methodology, emphasizing the design rationale for test cases and the observational analysis of experimental results. We will explore how designed test cases trigger ECN threshold changes in dynamic network environments, ensuring comprehensive and effective testing.
A key insight from our research is the critical role of qp-fairness (Queue Pair fairness) in collective benchmarking, alongside traditional metrics like algorithmic bandwidth and bus bandwidth. Through comparative analysis of real-world test data, we demonstrate how maintaining qp-fairness under dynamic conditions significantly enhances the stability of ECN mechanisms and ensures equitable allocation of network resources. By aligning theoretical insights with practical implementations, we hope to provide actionable insights for advancing research and applications in dynamic ECN technologies.
