通过改变队列节点的分组容量影响性能测量- DRED

Jafar Ababneh
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引用次数: 0

摘要

本文探讨了队列节点分组容量的变化对拥塞算法性能的影响。动态随机早降(DRED)算法是网络拥塞管理、预测和选择最优包数的关键。采用两个性能指标来评估不同分组容量的影响,即吞吐量和平均排队延迟。研究了队列节点不同容量的可塑性和有效性,并比较了队列节点不同分组容量的性能。就吞吐量而言,第一个队列节点比第二个队列节点执行得更有效,而第二个队列节点在这两项指标上都优于第三个队列节点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Influencing Performance Measurements through Varying Packet Capacities of Queue Nodes - DRED
This paper explores the impact of changes to the packet capacities of queue nodes on the performance of congestion algorithms. The dynamic random early drop (DRED) algorithm is crucial in managing congestion, predicting it, and selecting the optimal packet number. Two performance measures were employed to evaluate the effect of varying packet capacities, namely throughput and average queuing delay. Plasticity and efficacy of varying capacities of queue nodes was examined, and varying packet capacities of queue nodes were compared to assess performance. The first queue node performed more effectively than the second queue node in terms of throughput, while the second queue node outperformed the third queue node on both measures.
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