Random early detection gateways for congestion avoidance
IEEE/ACM Transactions on Networking (TON)
Computational Intelligence: An Introduction
Computational Intelligence: An Introduction
Fuzzy Logic Congestion Control in TCP/IP Tandem Networks
ISCC '06 Proceedings of the 11th IEEE Symposium on Computers and Communications
Effective control of traffic flow in ATM networks using fuzzy explicit rate marking (FERM)
IEEE Journal on Selected Areas in Communications
IEEE Network: The Magazine of Global Internetworking
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Network congestion control is a complex problem that requires robust, possibly intelligent, control methodologies to obtain satisfactory performance. Designing effective congestion control strategies for computer networks is known to be hard because of the difficulty of obtaining realistic, cost effective, tractable analytical models. This renders the application of classical control system design methods, which rely on availability of these models, very hard, and possibly not cost effective. Computational Intelligence employing Fuzzy Logic Control methodology is reported to offer effective solutions for certain classes of control problems. It is particularly appealing in non-linear complex systems where satisfactory analytic models are costly or impractical to obtain, but where their behaviour is well understood and can be captured by linguistic models. Consequently, a number of researchers have looked at fuzzy logic in order to devise effective, robust congestion control techniques. In this paper, we discuss several control approaches currently in use, before we motivate the utility of Fuzzy Logic based control. Then, through a number of examples, we illustrate the power of the methodology by the successful application of fuzzy based congestion control in the two diverse networking technologies of ATM and TCP/IP.