Robust congestion control for TCP/AQM using integral backstepping control

Loss differentiation is recommended as a service differentiation provided by an assured forwarding (AF) per-fop behavior (PHB) in differentiated service (DiffServ) architecture. An active queue management (AQM) technique is addressed as a suitable alternative to realize the service differentiation because the AF PHB should attempt to minimize long-term congestion while permitting short-term congestion in order to accommodate traffic bursts. In order to realize the AF PHB using an AQM scheme, it is desirable that the AQM scheme has DVO properties of sheltering and load tolerance in order to protect low drop precedence traffic and to prevent starvation of high drop precedence traffic. In this paper, we introduce another desirable property of assured drop probability. We modify an existing AQM algorithm for the property so that it assures a target drop probability in a properly provisioned network. Other properties of sheltering and load tolerance still hold for the modified AQM scheme. We evaluate it with other comparable schemes, i.e., WRED and RIO through simulation.

Design of a fuzzy controller for active queue management

This paper is concerned with the design of robust active queue management (AQM) controllers for a class of TCP networks. In TCP/IP networks, the packet-dropping probability function is limited between 0 and 1. Therefore, a TCP network with AQM controller was modeled as a rate-based non-linear system with a saturated input. The nonlinear output feedback AQM controller is proposed for achieving the desired queue size and guaranteeing asymptotic stability of the operating point. The performance and effectiveness of the proposed control laws are validated for serial network scenarios through numerical simulations by Network Simulator-2 (NS-2). Simulation results confirm that the proposed scheme outperforms other AQM schemes.

A study of robust active queue management schemes for correlated traffic

Denial of service (DoS) attacks are currently one of the biggest risks any organization connected to the Internet can face. Hence, the congestion handling techniques at its edge router(s), such as active queue management (AQM) schemes must consider possibilities of such attacks. Ideally, an AQM scheme should (a) ensure that each network flow gets its fair share of bandwidth, and (b) identify attack flows so that corrective actions (e.g. drop flooding traffic) can be explicitly taken against them to further mitigate the DoS attacks. This paper presents a proof-of-concept work on devising such an AQM scheme, which we name Deterministic Fair Sharing (DFS). Most of the existing AQM schemes do not achieve the above goals or have a significant room for improvement. DFS uses the concept of weighted fair share (wfs) which allows it to dynamically self-adjust the router buffer usage based on the current level of congestion, while assuring fairness among flows and aiding in identifying the malicious ones. We demonstrate the performance of DFS via extensive simulation and compare against other existing AQM techniques.

In this paper, we propose a Takagi-Sugeno (T-S) fuzzy controller for active queue management (AQM) with explicit congestion notification (ECN) to improve the performance of Internet communications. We use the queue length and incoming flow rate to measure the degree of congestion effect on Internet to regulate the queue length at a specified level. Linear matrix inequality (LMI) techniques are employed to obtain the feedback gains. To proceed farther into the verification of proposed scheme, we make use of the network simulation (NS-2) in our experiment. Comparing with other AQM schemes, the experiment results show that the proposed AQM has better performance in terms of packet loss, throughput and the fluctuation of queue length.

An efficient active queue management (AQM) controller for a class of stochastic TCP communication networks is proposed in this study. By applying the Lyapunov-Krasovskii functional approach and the linear matrix inequality (LMI) technique, a static-state-feedback controller (SSFC) capable of both achieving the desired queue size and guaranteeing asymptotic stability of the operating point is presented. A series of numerical simulations are discussed in various network environments to evaluate the proposed scheme. The simulation results show that the proposed schemes surpass other AQM schemes.

Several active queue management (AQM) schemes have been proposed to address the bufferbloat issue, a long network delay and performance degradation issue caused by excess buffering of packets in network nodes. The solutions proposed up to now, however, satisfy only a subset of the key network performance metrics, i.e., end-to-end throughput, throughput fairness, and delay, in 802.11s-based multi-radio multi-channel wireless mesh networks (MRMC WMN). In this letter, we propose FD-AQM, a fairness-aware delay-controlled AQM to satisfy all three key network performance metrics simultaneously in the 802.11s-based MRMC WMN. The proposed FD-AQM achieves the goal by adopting a per-queue drop interval which is recalibrated according to the average round-trip time of flows, and a drop decision mechanism which considers average throughput as well as target delay. Through simulations, we show that FD-AQM is superior to other AQM schemes in terms of throughput and fairness.

We present a virtual queue-based active queue management (AQM) scheme, called stabilized virtual buffer (SVB). The SVB scheme uses the packet arrival rate and queue length information to drop/mark packets probabilistically in a congested Internet router. System goodput, packet loss rate, average queue length, and stability of the queue are used to compare the proposed SVB scheme with prior AQM schemes (RED - random early detection; REM - random exponential marking; AVQ - adaptive virtual queue). Simulation results indicate that the SVB algorithm can provide better goodput and lower loss rate than the other three AQMs. The most striking feature of the proposed scheme is its robustness to workload fluctuations in maintaining a stable queue for different workload mixes (short and long flows) and parameter settings.

Congestion control in TCP/AQM networks is expected to perform well for a wide-range of conditions, but recent advances in modeling and analysis indicate that present AQM (active queue management) schemes need an extra dose of adaptability to cope. The paper answers the call and proposes a self-tuning structure wherein AQM parameters are automatically tuned in response to on-line estimation of link capacity and traffic load. This approach is applicable to any AQM scheme that is parameterizable in terms of link capacity and TCP load. We describe this self-tuning structure, illustrate its application to PI (proportional-integral) and RED (random early detection) AQMs, provide stability analysis, and conduct ns simulations to compare with both fixed AQM schemes and the recently proposed adaptive RED.

One of the challenges in the design of switches/routers is the efficient and fair use of the shared bottleneck bandwidth among different Internet flows. In particular, various active queue management (AQM) schemes have been developed to regulate transmission control protocol traffic in response to router congestion. In addition, in order to provide fair bandwidth sharing, these AQM must protect the well-behaved flows from the misbehaving flows. However, most of the existing AQM schemes cannot provide accurate fair bandwidth sharing while being scalable. The key to the scalability and fairness of the AQM schemes is the accurate estimation of certain network resources without keeping too much state information. We propose a novel technique to estimate two network resource parameters: the number of flows in the buffer and the data source rate of a flow by using a capture-recapture (CR) model. The CR model depends on simply the random capturing/recapturing of the incoming packets, and as a result, it provides a good approximation tool with low time/space complexity. These network resource parameters are then used to provide fair bandwidth sharing among the Internet flows. Our experiments and analysis will demonstrate that this new technique outperforms the existing mechanisms and closely approximates the ideal case, where full state information is needed.

This paper proposes a partial state Active Queue Management (AQM) technique, called CHOKe-FS, which addresses the problem of fair-bandwidth allocation among different flows sharing a common bottleneck link. CHOKe-FS is a packet-dropping mechanism for classifying and restricting unresponsive or misbehaving flows during congestion. It utilizes a direct bitmap technique, which estimates the number of active flows in the buffer to compute the fair-share. It inherits the matched drop mechanism of CHOKe and the buffer management technique of RED. The proposed technique differs from CHOKe in three ways: (i) it divides the queue into multiple regions, (ii) it dynamically adjusts the drawing factor depending on the average queue occupancy, by drawing multiple packets from the buffer, and (iii) it estimates the number of active flows in a queue for fair share estimation to drop the packet from flows exceeding the fair bandwidth share. The performance of CHOKe-FS is analyzed under various scenarios by comparing it with the well-known, AQM schemes such as RED, CHOKe and CHOKeR. The results demonstrate that the proposed algorithm not only protects the responsive flows from unresponsive flows, but it also works reasonably well for providing intra-protocol fairness.

A comparative simulation study of TCP/AQM systems for evaluating the potential of neuron-based AQM schemes

Anti-windup compensator for active queue management in TCP networks

We proposed a parameter-tunable robust proportional-integral-differential (PID) controller for active queue management (AQM) based on modern H∞ optimal control theory in [12]. Our robust PID controller can be tuned only by one parameter unlike traditional PID controllers, which are tuned by three or more. Additionally, this new parameter assignment method can be extended to other controller designed for AQM scheme based on classical control theory or optimal control theory. In this paper, we present an analysis and implementation study on it. Taken both robustness and closed loop performance into considerations, most desirable parameters value can be identified by the analytical formulas derived by us. Theoretical analysis shows that the proposed controller can converge to the reference value in steady state. Simulation results confirm our expectation that our PID controller for AQM outperforms the existing well-known congestion controllers, such as RED and PI controller, on keeping the router queue size at the target value without queue vibration. Further, the most important feature is that the controller is robust to the network dynamics and traffic load changes.