Stochastic Fair Traffic Management for Efficient and Robust IP Networking

Abstract

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.