Robust control tools for traffic monitoring in TCP/AQM networks

Several studies have considered control theory tools for traffic control in communication networks, as for example the congestion control issue in IP (Internet Protocol) routers. In this paper, we propose to design a linear observer for time-delay systems to address the traffic monitoring issue in TCP/AQM (Transmission Control Protocol/Active Queue Management) networks. Due to several propagation delays and the queueing delay, the set TCP/AQM is modeled as a multiple delayed system of a particular form. Hence, appropriate robust control tools as quadratic separation are adopted to construct a delay dependent observer for TCP flows estimation. Note that, the developed mechanism enables also the anomaly detection issue for a class of DoS (Denial of Service) attacks. At last, simulations via the network simulator NS-2 and an emulation experiment validate the proposed methodology

Détection et estimation d'anomalies dans un réseau de communication

La supervision des réseaux de communication et plus particulièrement la détection d'anomalies représente un aspect important de la Qualité de Service. Les anomalies sont des circonstances où certaines opérations dévient de leur comportement normal. Certaines sont causées par des problèmes physiques ou techniques comme la panne d'électricité ou les échecs de serveur de fichier, des changements brusques causés par le trafic légitime comme la surcharge du réseau, les foules subites, ainsi que des comportements risqués illégitimes comme des attaques de Déni de Service (DdS) et Déni de Service Distribué (DddS). Nous confrontons la problématique de détection et reconstruction des anomalies parvenant au modèle TCP/IP par la théorie de commande. Ces anomalies sont considérées comme des défauts dans un modèle mathématique représentant la dynamique du modèle TCP/IP. Dans le domaine de détection des défauts, les observateurs peuvent être classés, selon la connaissance du profil des défauts, en observateurs à entrée connue ou à entrée inconnue. Notre première contribution en termes de synthèse d'observateurs à entrées connues se limite à des formes polynômiales pouvant recouvrir une large gamme d'anomalies. L'anomalie et ses dérivées successives introduites dans l'espace d'état du système sont reconstruites par des observateurs de Luenberger. La construction des observateurs étant contraignante en termes de formes spécifiques de l'anomalie et le degré du polynôme associé, une autre approche traitant la détection des anomalies complètement inconnues est proposée. Les modes glissants d'ordre un et d'ordre supérieur sont conçus pour le modèle TCP pour garantir une convergence en temps fini et la robustesse vis-à-vis des incertitudes paramétriques et des défauts. Nos propositions sont étudiées de manière analytique par des validations sous Matlab/Simulink et le Simulateur de Réseaux NS-2. De plus, dans le contexte de NS-2, ces dernières approches sont intégrées dans un module de rejeu des traces de trafic afin de les tester sur un trafic TCP capturé en environnement réel.The supervision domain particularly the anomaly detectionrepresents an important aspect of guaranteeing a Quality of Serviceto communication networks. A wide variety of disruptions designated as anomalies are often related to physical or technical problems such as power or file server failures, abrupt changes caused by legitimate traffic such as network congestion or flash crowds, and risky illegitimate behavior such as Denial-of-Service and Distributed Denial of Service (DoS/DDoS) attacks. We address the problem of anomalies detection and reconstruction in TCP/IP model based on control theory techniques. These anomalies are considered as fault signals in the mathematical model adopted for representing TCP/IP dynamics. For faults detection and according to our knowledge of the faults variations, the observers may be classified into known or unknown input observers. Our first contribution in terms of conceiving known input observers is limited to polynomial forms able to cover a wide range of anomalies. The anomaly and its derivatives are reconstructed by Luenberger observersafter introducing them in the state space of the system. The construction of these latter observers is limited in terms of specific anomaly profiles and constrained by the polynomial degree associated to the anomaly. Therefore, another detection approach dealing with completely unknown anomalies is proposed. The sliding modes first and higher orders are investigated to guarantee finite time convergence and robustness against parametric uncertainties and faults. Our proposals have been studied analytically by validating via Matlab/Simulinkand the Network SimulatorNS-2. Furthermore, in the context of NS-2, these approaches are integrated into a module for replaying traffic traces in order to test them on a TCP traffic captured in real environment

Détection et estimation d'anomalies dans un réseau de communication

TOULOUSE3-BU Sciences (315552104) / SudocSudocFranceF

Adaptive sliding mode-based diagnosis of actuator faults for LPV systems

In this paper, an adaptive sliding mode observer is developed for actuator fault diagnosis of linear parameter-varying systems. The main advantage of the proposed approach is its ability to cope with time-varying distribution matrix in linear parameter-varying systems. Furthermore, the proposed adaptive observer is characterized by its output robustness against parameter uncertainties and disturbances without any a priori knowledge about their bounds. The efficiency of the proposed fault diagnosis approach is validated using simulation studies. Copyright 1 2017 John Wiley & Sons, Ltd.This publication was made possible by NPRP grant 5-574-2-233 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.Scopu

Sliding Modes for Anomaly Observation in TCP Networks: From Theory to Practice

International audienceAnomaly detection has been an active open problem in the networks community for several years. In this brief, we aim at detecting such abnormal signals by control theory techniques. Several classes of sliding mode observers are proposed for a fluid flow model of the transmission control protocol (TCP)/internet protocol network. Comparative simulations via network simulator NS-2 show the enhancement brought by a higher order sliding mode observer. The efficiency of this observer opens the way toward observing traffics with real TCP flow characteristics. To achieve this end, trace replay techniques for TCP traffic traces are presented. Finally, experiments lead to successful anomaly estimation under real traffic conditions

Second order sliding mode observer for anomaly detection in TCP networks: from theory to practice

International audienc

Reduced LPV Modeling and Control of a Solution Copolymerization Reactor

Controlling the operation of polymer reactors is a highly important task that aims at maximizing the production rate and the product quality and also minimizing the transition losses due to the high consumer demands, as well as the tight market competition for producing different grades of polymers. However, the control design task is nontrivial due to the nonlinear behavior of polymer reactor systems which exhibit strong dependence on multiple operating regimes, unstable modes at some operating points as well as time-varying parameters. In this work, linear parameter-varying (LPV) control techniques are considered to control a free radical solution copolymerization reactor. LPV systems describe a class of nonlinear/time-varying systems that can be represented in terms of parameterized linear dynamics in which the model coefficients depend on a number of measurable variables called scheduling variables. The LPV controller synthesis tools extend the well-known methods of controlling linear time-invariant (LTI) systems to control nonlinear systems with guaranteed stability and high performance over a wide range of operation. In this work, the LPV representation of the copolymerization reactor is obtained through a transformation capturing the system nonlinearities in 15 scheduling variables. With this high number of scheduling variables, the design of LPV controller involves two major problems. On one hand, for control synthesis design, the number of linear matrix inequalities (LMIs) to be solved increases exponentially with the number of scheduling variables, hence the problem becomes computationally intractable. On the other hand, overbounding the range of the scheduling variables often renders the LPV model to include some behaviors that are not exhibited by the original plant, which results in conservatism. In order to cope with the high number of scheduling variables, two approaches for reduced LPV model development for the copolymerization reactor are introduced. The aim of this work is to emphasize the capability of the LPV controllers, designed on the basis of reduced models, to provide high performance control of the polymerization reactor by enhancing the settling time of the output and reducing the control effort. In the first approach, the number of scheduling variables is reduced via the parameter set mapping (PSM) procedure based on principal component analysis (PCA). PSM is an effective way to reduce the conservatism in LPV modeling by resizing the scheduling range such that the reduced model matches the original system behavior as closely as possible. With this method, the complexity of the LPV model of the copolymerization reactor is ideally reduced into one scheduling variable, which allows a minimal design complexity. However, the synthesized controllers may not guarantee the closed-loop stability and performance with the full nonlinear model of the copolymerization reactor since they are designed based on an approximation of the nonlinear model. The second method is based on an alternative conversion of the nonlinear model to an LPV form by truncating the state variables that have no significant role in the state evolution. This method is a specific model reduction approach aiming at reducing the complexity, as well as the number of scheduling variables of the model while the input-output behavior of the original system is preserved. The resulting reduced LPV model of the copolymerization reactor has 4 scheduling variables, which is a relatively large number. However, the stability and performance of the original plant are guaranteed with such controller. Once the operating region and the resulting LPV models are determined, a control design methodology is applied on each produced model. For the LPV-PSM approach, LPV H_infty control synthesis is used to synthesize an LPV controller for the reduced LPV model of the reactor. For the reduced order based model, a linear fractional transformation (LFT) based LPV controller synthesis approach is used since it is capable of handling plants with relatively large number of scheduling variables while maintaining low design complexity. However, the implementation of the designed LPV controllers requires the availability of all the scheduling variables, some of which are not measurable in the reactor model. Therefore, an extended Kalman filter (EKF) is designed for the nonlinear model of the copolymerization reactor in order to estimate its state vector. A comparative analysis of the closed-loop performance is done between the synthesized LPV controllers and the model predictive controller (MPC) developed in the literature. The PSM based LPV controller, based on one scheduling dimension LPV model, has shown a better disturbance rejection without either output oscillation or input saturation and a convergence time of 9 hours, which is lower than the reduced order based LPV controller and the MPC controller whose convergence times are 10 hours and 15 hours, respectively. This enhancement in the closed-loop performance is due to the low conservatism of the design by the PSM approach. However, the inability to guarantee the closed-loop stability with the nonlinear reactor model remains the main drawback of the PSM procedure, whereas the stability is guaranteed with the LPV controller based on reduced order LPV model. As a conclusion, a trade-off is illustrated by the low complexity and good performance on one hand, and the stability guarantee of the closed-loop system with the nonlinear model of the reactor on other hand.qscienc

Détection de Dénis de Service (DdS) dans une architecture TCP par un observateur glissant

National audienc

Second order sliding mode observer for anomaly detection in TCP networks: from theory to practice

International audienc

Traffic monitoring in TCP/AQM networks through a time delay observer

International audienceThe use of the control theory tools for traffic control in communication networks, e.g. the congestion control in IP (Internet Protocol) routers, has given rise to challenging issues in the time-delay system framework. In this paper, we propose to design a linear time-delay observer for traffic monitoring in TCP/AQM (Transmission Control Protocol/Active Queue Management) networks. More precisely, we focus on a bottleneck topology consisting of long-lived TCP communications through a controlled router. The developed mechanism, located at the router, aims at supervising the network via TCP flow estimations as well as detecting anomalies for a class of DoS (Denial of Service) attacks. This issue is formulated as a stability problem for multiple delayed systems and appropriate robust control tools such as quadratic separation are adopted to address it. Then, some simulations via the network simulator NS-2 and an emulation experiment support the proposed methodology