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

Design of Feedback Controls Supporting TCP Based on the State–Space Approach

This paper investigates how to design feedback controls supporting transmission control protocol (TCP) based on the state-space approach for the linearized system of the well-known additive increase multiplicative decrease (AIMD) dynamic model. We formulate the feedback control design problem as state-space models without assuming its structure in advance. Thereby, we get three results that have not been observed by previous studies on the congestion control problem. 1) In order to fully support TCP, we need a proportional-derivative (PD)-type state-feedback control structure in terms of queue length (or RTT: round trip time). This backs up the conjecture in the networking literature that the AQM RED is not enough to control TCP dynamic behavior, where RED can be classified as a P-type AQM (or as an output feedback control for the linearized AIMD model). 2) In order to fully support TCP in the presence of delays, we derive delay-dependent feedback control structures to compensate for delays explicitly under the assumption that RTT, capacity and number of sources are known, where all existing AQMs including RED, REM/PI and AVQ are delay-independent controls. 3) In an attempt to interpret different AQM structures in a unified manner rather than to compare them via simulations, we propose a PID-type mathematical framework using integral control action. As a performance index to measure the deviation of the closed-loop system from an equilibrium point, we use a linear quadratic (LQ) cost of the transients of state and control variables such as queue length, aggregate rate, jitter in the aggregate rate, and congestion measure. Stabilizing gains of the feedback control structures are obtained minimizing the LQ cost. Then, we discuss the impact of the control structure on performance using the PID-type mathematical framework. All results are extended to the case of multiple links and heterogeneous delays

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

Active queue management with discrete sliding modes in TCP networks

In this paper, a new active queue management (AQM) algorithm for data traffic control in TCP/IP networks is developed. The algorithm design is based on the principles of discrete sliding-mode control. Unlike majority of earlier studies, the design procedure considers the effects of both non-negligible delay in transferring data and feedback information and unpredictable capacity variations. The switching function is selected to incorporate a delay compensation mechanism, which ensures efficient network operation even for large bandwidthdelay product connections. The proposed algorithm, implemented as a packet marking scheme, is tested in discrete event ns-2 simulator. The results show that the algorithm provides fast convergence to steady state after sudden, unanticipated capacity changes. By generating smaller overshoots, the proposed algorithm also allows for reducing buffer space requirements to avoid packet loss as compared to the benchmark AQM solutions

Design of a robust Controller/Observer for TCP/AQM network: First application to intrusion detection systems for drone fleet

International audienceThis paper proposes a robust controller/observer for UAVs network anomaly estimation which is based on both Lyapunov Krasovkii functional and dynamic behavior of TCP (Transmission Control Protocol). Several research works on network anomaly estimation have been led using automatic control techniques and provide methods for designing both observer and command laws dedicated to time delay problem while estimating the anomaly or intrusion in the system. The observer design is based on a linearized fluid-flow model of the TCP behavior and must be associated to an AQM (Active Queue Management) to perform its diagnosis. The developed robust controller/observer in this paper has to be tuned by considering the time delay linear state-space representation of TCP model. As a first result, the designed controller/observer system has been successfully applied to some relevant practical problems such as topology network for aerial vehicles and the effectiveness is illustrated by using real traffic traces including Denial of Service attacks. Our first results show promising perspectives for Intrusion Detection System (IDS) in a fleet of UAVs

Proportional-integral genetic algorithm controller for stability of TCP network

The life development and increase the number of internet users imposed an increase in data circulating on the internet network and then make the network more congestion. As a result of all this, some problems arose such as time delay in packets delivery, loss of packets, and exceed the buffer capacity for the middle routers. To overcome those problems, transmission control protocol and active queue management (TCP/AQM) have been used. AQM is the main approach used to control congestion and overcome those problems to improve network performance. This work proposes to use the proportional-integral (PI) controller with a genetic algorithm (GA) as an active queue manager for routers of the Internet. The simulation results show a good performance for managing the congestion with using proportional-integral genetic algorithm (GA-PI) controller better than the PI controller

GA-PSO-Optimized Neural-Based Control Scheme for Adaptive Congestion Control to Improve Performance in Multimedia Applications

Active queue control aims to improve the overall communication network throughput while providing lower delay and small packet loss rate. The basic idea is to actively trigger packet dropping (or marking provided by explicit congestion notification (ECN)) before buffer overflow. In this paper, two artificial neural networks (ANN)-based control schemes are proposed for adaptive queue control in TCP communication networks. The structure of these controllers is optimized using genetic algorithm (GA) and the output weights of ANNs are optimized using particle swarm optimization (PSO) algorithm. The controllers are radial bias function (RBF)-based, but to improve the robustness of RBF controller, an error-integral term is added to RBF equation in the second scheme. Experimental results show that GA- PSO-optimized improved RBF (I-RBF) model controls network congestion effectively in terms of link utilization with a low packet loss rate and outperform Drop Tail, proportional-integral (PI), random exponential marking (REM), and adaptive random early detection (ARED) controllers.Comment: arXiv admin note: text overlap with arXiv:1711.0635

Symbolic dynamical model of average queue size of random early detection algorithm

In this paper, a symbolic dynamical model of the average queue size of the random early detection (RED) algorithm is proposed. The conditions on both the system parameters and the initial conditions that the average queue size of the RED algorithm would converge to a fixed point are derived. These results are useful for network engineers to design both the system parameters and the initial conditions so that internet networks would achieve a good performance