Fuzzy control and fuzzy systems (2nd, extended ed.)
Fuzzy control and fuzzy systems (2nd, extended ed.)
Dynamics of random early detection
SIGCOMM '97 Proceedings of the ACM SIGCOMM '97 conference on Applications, technologies, architectures, and protocols for computer communication
Proceedings of the conference on Applications, Technologies, Architectures, and Protocols for Computer Communication
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
The drop from front strategy in TCP and in TCP over ATM
INFOCOM'96 Proceedings of the Fifteenth annual joint conference of the IEEE computer and communications societies conference on The conference on computer communications - Volume 3
ACSC '05 Proceedings of the Twenty-eighth Australasian conference on Computer Science - Volume 38
A proactive mechanism for quality of service control in high speed networks
International Journal of Business Information Systems
A robust active queue management algorithm in large delay networks
Computer Communications
Semi-supervised detrended correspondence analysis algorithm
IITA'09 Proceedings of the 3rd international conference on Intelligent information technology application
A packet dropping strategy based on C-R model
IITA'09 Proceedings of the 3rd international conference on Intelligent information technology application
F-ECN: a loss discrimination based on fuzzy logic control
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 7
Design of a multi-model fuzzy controller for AQM
FSKD'06 Proceedings of the Third international conference on Fuzzy Systems and Knowledge Discovery
A new self-tuning active queue management algorithm based on adaptive control
NPC'05 Proceedings of the 2005 IFIP international conference on Network and Parallel Computing
Active queue management via event-driven feedback control
Computer Communications
| Hi-index | 0.24 |
As an effective mechanism acting on the intermediate nodes to support end-to-end congestion control, active queue management (AQM) takes a trade-off between link utilization and delay experienced by data packets. From the point of view of the control theory, it is rational to regard AQM as a typical regulating system. Although proportional integral (PI) controller for AQM outperforms traditional RED algorithm, the mismatches in simplified TCP flow model inevitably degrades the performance because the design of PI controller is heavily dependent of the accuracy of the plant, such as, for small buffer the system tends to perform poorly. In this paper, the fuzzy logic controller (FLC) for AQM is designed based on the fuzzy logical control. Its superiority is independent of the model of the plant, which is very suitable to the high variability and uncertainty networks. We present the guidelines and highlights to design the parameters of the FLC. We then compare its performance with the PI controller through simulations, and investigate the impact of the network configuration and operating parameters on the stability and responsibility. The results show that the FLC is rather robust against the noise and disturbance caused by the round-trip time, the link capacity, the number of the active flows and the non-responsive UDP flows, etc., which badly degrade the performance of the PI controller. The transient response and tracking capability of the FLC is superior to that of the PI controller, which is beneficial to achieve the goals of AQM scheme.