A genetic algorithm for the design of a fuzzy controller for active queue management

Active queue management (AQM) policies are those policies of router queue management that allow for the detection of network congestion, the notification of such occurrences to the hosts on the network borders, and the adoption of a suitable control policy. This paper proposes the adoption of a fuzzy proportional integral (FPI) controller as an active queue manager for Internet routers. The analytical design of the proposed FPI controller is carried out in analogy with a proportional integral (PI) controller, which recently has been proposed for AQM. A genetic algorithm is proposed for tuning of the FPI controller parameters with respect to optimal disturbance rejection. In the paper the FPI controller design metodology is described and the results of the comparison with random early detection (RED), tail drop, and PI controller are presented

Dsrem Regulator in the Tcp/ip Network

The paper presents the main parameters and describes the behavior of the active queue management (AQM) algorithm which based on random exponential marking (REM) packets in TCP/IP network. It has presented the new AQM algorithm, which has been developed by author, which is based on REM and uses dynamically splitting marking characteristic (DSREM) of network packets. The basic parameters and functional principle of DSREM algorithm have been shown. Block diagram of linearized AQM system, which is based on DSREM management law and describes its main components, is shown. Transfer characteristic for DSREM, which is based on the Laplace transform and its basic parameters, are considered. Simulation of TCP/IP network, which contains congested link for small and large sources of incoming messages using REM and DSREM regulators, is done. Log-frequency characteristics for REM and DSREM methods are obtained and their comparative analysis is performed. It is concluded that the regulator based on DSREM algorithm has better performance and stability of the system can be used in the AQM system

A quantitative analysis and performance study of fast congestion notification (FN) mechanism

Congestion in computer network happens when the number of transmission requests exceeds the transmission capacity at a certain network point (called a bottle-neck resource) at a specific time. Congestion usually causes buffers overflow and packets loss. The purpose of congestion management is to maintain a balance between the transmission requests and the transmission capacity so that the bottle-neck resources operate on an optimal level, and the sources are offered service in a way that assures fairness. Fast Congestion Notification (FN) is one of the proactive queue management mechanisms that limits the queuing delay and achieves the maximum link utilization possible with minimum packet drops. In this paper we present a detailed performance comparison of the Linear FN algorithm to RED based on the results obtained through simulations. The paper shows how FN can be tuned for different window size (Ws) and periods of time constant (T) to achieve higher link utilization; reduce the queuing delay, and lower packet drop ratio

Maximum Production Of Transmission Messages Rate For Service Discovery Protocols

Minimizing the number of dropped User Datagram Protocol (UDP) messages in a network is regarded as a challenge by researchers. This issue represents serious problems for many protocols particularly those that depend on sending messages as part of their strategy, such us service discovery protocols. This paper proposes and evaluates an algorithm to predict the minimum period of time required between two or more consecutive messages and suggests the minimum queue sizes for the routers, to manage the traffic and minimise the number of dropped messages that has been caused by either congestion or queue overflow or both together. The algorithm has been applied to the Universal Plug and Play (UPnP) protocol using ns2 simulator. It was tested when the routers were connected in two configurations; as a centralized and de centralized. The message length and bandwidth of the links among the routers were taken in the consideration. The result shows Better improvement in number of dropped messages `among the routers