Fuzzy predictive preferential dropping for active queue management

Authors:
Lichang Che;Bin Qiu
Affiliations:
School of Computer Science and Software Engineering, Monash University, Vic, Australia;School of Computer Science and Software Engineering, Monash University, Vic, Australia
Venue:
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part II
Year:
2005

Citing 4
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Abstract

This paper proposes an Active Queue Management(AQM) scheme referred to as Fuzzy Predictive Preferential Dropping (FPPD). Two contributions are made in this work. Firstly, a fuzzy predictor is employed to improve the accuracy of traffic prediction. Secondly, a novel congestion index, predicted traffic intensity from fast flows, is used to derive packet dropping probability for AQM. The FPPD safely detects real congestion caused by large flows while leaving transient traffic burst from short-lived flows alone. Furthermore, a preferential dropping mechanism is adopted to treat packets from long-term fast flows and short-lived flows differently. Simulations show that the proposed FPPD reduces packet drop ratio and utilizes link bandwidth more efficiently than other AQM schemes. It also improves the quality of service perceived by web users.