高效鲁棒IP网络的随机公平流量管理

J. Chung, M. Claypool, R. Kinicki
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引用次数: 2

摘要

随着非tcp应用程序(如流媒体和网络游戏)的使用增加,不公平、行为不端的流和拥塞崩溃的威胁的可能性也在增加。本文介绍了一种统计流量过滤技术——随机公平监护人(SFG),它能在最小的流量状态信息下有效地调节不正常流量。SFG可以与主动队列管理(AQM)机制结合使用,以提高网络保护和效率。仿真用于评估SFG以及SFG与比例积分(PI)控制器的集成,并与其他类似的统计流量管理机制(包括RED-PD, SFB和CHOKe)进行比较。在广泛的实际流量负载和条件下,SFG-PI组合在公平性、排队延迟、稳定性和TCP性能方面优于其他机制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Stochastic Fair Traffic Management for Efficient and Robust IP Networking
As use of non-TCP applications such as streaming media and network games increases, the potential for unfair, misbehaving flows and the threat of congestion collapse also increases. This paper introduces a statistical traffic filtering technique, stochastic fairness guardian (SFG), that effectively regulates misbehaving flows with minimal traffic state information. SFG can be used in conjunction with an active queue management (AQM) mechanism to improve both network protection and efficiency. Simulations are used to evaluated SFG and the integration of SFG with a proportional-integral (PI) controller in comparison with other similar statistical flow management mechanisms including RED-PD, SFB and CHOKe. The SFG-PI combination outperforms other mechanisms in terms of fairness, queuing delay, stability and TCP performance over a wide range of realistic traffic loads and conditions.
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