A new self-tuning active queue management algorithm based on adaptive control

Authors:
Heying Zhang;Baohong Liu;Liquan Xiao;Wenhua Dou
Affiliations:
School of Computer, National University of Defense Technology, Changsha, Hunan, China;Institute of Automation, National University of Defense Technology, Changsha, Hunan, China;School of Computer, National University of Defense Technology, Changsha, Hunan, China;School of Computer, National University of Defense Technology, Changsha, Hunan, China
Venue:
NPC'05 Proceedings of the 2005 IFIP international conference on Network and Parallel Computing
Year:
2005

Citing 4
Cited 0

Random early detection gateways for congestion avoidance

IEEE/ACM Transactions on Networking (TON)
Fluid-based analysis of a network of AQM routers supporting TCP flows with an application to RED

Proceedings of the conference on Applications, Technologies, Architectures, and Protocols for Computer Communication
Design of a robust active queue management algorithm based on feedback compensation

Proceedings of the 2003 conference on Applications, technologies, architectures, and protocols for computer communications
Design of a fuzzy controller for active queue management

Computer Communications

Quantified Score

Hi-index	0.00

Visualization

Abstract

Most Active Queue Management (AQM) algorithms based on control theory have difficulty in obtaining desirable performance once the network conditions or the traffic patterns change out of the presumed ones they are designed for. To address these problems, a new self-tuning AQM algorithm called STR is proposed in this paper. STR has the ability of keeping minimum variance between the instantaneous queue length of the router and the reference value by estimating the parameters of the model of controlled object online and adjusting the packet drop probability accordingly. The performance of STR is evaluated through extensive simulations. The results show that STR is robust against the great changes of the network parameters and the traffic load.