Conference Paper

Fuzzy explicit marking for congestion control in differentiated services networks

Dept. of Comput. Sci., Cyprus Univ., Nicosia, Cyprus
DOI: 10.1109/ISCC.2003.1214139 Conference: Computers and Communication, 2003. (ISCC 2003). Proceedings. Eighth IEEE International Symposium on
Source: DBLP


This paper presents a new active queue management scheme, fuzzy explicit marking (FEM), implemented within the differentiated services (Diffserv) framework to provide the congestion control using a fuzzy logic control approach. Network congestion control remains a critical and high priority issue. The rapid growth of the Internet and increased demand to use the Internet for time-sensitive voice and video applications necessitate the design and utilization of effective congestion control algorithms, especially for new architectures, such as Diffserv. As a result, a number of researchers are now looking at alternatively schemes to TCP congestion control. RED (random early detection) and its variants are one of these alternatives to provide quality of service (QoS) in TCP/IP Diffserv networks. The proposed fuzzy logic approach for congestion control allows the use of linguistic knowledge to capture the dynamics of nonlinear probability marking functions and offer effective implementation, use of multiple inputs to capture the (dynamic) state of the network more accurately, enable finer tuning for packet marking behaviors (either dropping a packet or setting its ECN - explicit congestion notification - bit) for aggravated flows, and thus provide better QoS to different types of data streams, such as TCP/FTP traffic or TCP/Web-like traffic, whilst maintaining high utilization.

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    • "Fuzzy control may be viewed as a way of designing feedback controllers [6], [5] in situations where rigorous control theoretic approaches can not be applied due to difficulties in obtaining formal analytical models. Linguistic variables, a key concept of fuzzy logic control, take on linguistic values which are words (linguistic terms) used to describe characteristics of the variables. "
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