Congestion control in differentiated services networks using fuzzy logic

Abstract

The provision of quality of service (QoS) in a differentiated services (Diff-Serv) environment requires an adequate differentiation between high-priority/assured and low-priority/best-effort classes of service in the presence of congestion, giving priority/preference to assured-tagged traffic. For this purpose, a new active queue management scheme, implemented within the Diff-Serv framework, is presented that provides congestion control in TCP/IP networks using a fuzzy logic control approach. The proposed fuzzy logic approach for congestion control allows the use of linguistic knowledge to capture the dynamics of nonlinear probability marking functions, uses multiple inputs to capture the dynamic state of the network more accurately, and can offer effective implementation. A simulation study over a wide range of traffic conditions - considering multiple bottleneck links - shows that the fuzzy logic based controller outperforms the random early detection (RED) implementation for Diff-Serv in terms of link utilization, packet losses, and queue fluctuations and delays. Also, the proposed scheme can offer better differentiation among assured and best-effort traffic, thus it can provide better QoS to different types of data streams, such as TCP/FTP traffic or TCP/Web-like traffic, whilst maintaining high utilization.