Random early detection gateways for congestion avoidance
IEEE/ACM Transactions on Networking (TON)
Dynamics of random early detection
SIGCOMM '97 Proceedings of the ACM SIGCOMM '97 conference on Applications, technologies, architectures, and protocols for computer communication
Optimization flow control—I: basic algorithm and convergence
IEEE/ACM Transactions on Networking (TON)
Modeling TCP Reno performance: a simple model and its empirical validation
IEEE/ACM Transactions on Networking (TON)
Simulation Comparison of RED and REM
ICON '00 Proceedings of the 8th IEEE International Conference on Networks
Fuzzy control of ABR traffic flow in ATM LANs
ISCC '95 Proceedings of the IEEE Symposium on Computers and Communications (ISCC'95)
Intelligent Congestion Control in ATM Networks
FTDCS '95 Proceedings of the 5th IEEE Workshop on Future Trends of Distributed Computing Systems
A duality model of TCP and queue management algorithms
IEEE/ACM Transactions on Networking (TON)
Effective control of traffic flow in ATM networks using fuzzy explicit rate marking (FERM)
IEEE Journal on Selected Areas in Communications
A rule-based intelligent multimedia streaming server system
Journal of Mobile Multimedia
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In this paper, we demonstrate an example of using artificial intelligent in solving problems with complex and uncertain features in communication networks. The concept of Fuzzy Expert System is used in the design of an Active Queue Management (AQM) algorithm. Expert System and Fuzzy Logic are commonly used methods in solving various kinds of uncertain problems. Network congestion control is a problem with large scale and complexity, where no accurate and reliable model has been proposed so far. We believe Fuzzy Expert System methods have the potential to be applied to congestion control and solve those problems with uncertainties. This research demonstrates the possibility of using Fuzzy Expert System in the network congestion control. In this paper, a fuzzy-expert-system-based structure is proposed for network congestion control and a novel AQM algorithm is introduced. Simulation experiments are designed to show that the fuzzy-expert-system-based AQM algorithm exhibits a better performance than conventional approaches.