A New Fuzzy Logic Approach for TCP Congestion Control

Congestion control is a high priority and critical issue in today’s networks. End-to-end congestion control mechanisms such as those in TCP are not enough to prevent congestion control and they must be supplemented by control mechanisms inside the network. In this paper we present a fuzzy logic approach for congestion control in TCP/IP networks. The proposed approach consists of three major parts: the Fuzzy Aggressive RTO Estimator (FARE), the Fuzzy Active Queue Management (Fuzzy AQM) and the Fuzzy Type 2 Scheduler. The FARE proposes an optimization of current RTO (retransmission TimeOut) estimation algorithm. By adding a detection mechanism for bad timeouts and undoing their side effects we are willing to have an aggressive estimator. By using a fuzzy system to adapt the K parameter of RTO estimation formula to network internal state, we try to answer the following questions: how much and when should our estimator act aggressively? On the other hand, the Fuzzy AQM computes the packet drop probability according to preconfigured fuzzy logic using the instantaneous queue length and number of packets dropped in a period of time as input variables. The Fuzzy Type 2 Scheduler uses the benefits of fuzzy type 2 controllers to adjust the service rate of the output buffers in the network routers. Our goal is to improve system performance and resource utilization in congested networks by a simple method. The simulation results with different web-like and FTP traffic show the superiority of TCP using FARE and Fuzzy AQM over a normal TCP. Furthermore it has been shown that the proposed Fuzzy Type 2 Scheduler has better performance than the traditional Weighted Round Robin (WRR) scheduler.