Adaptive AQM controllers for IP routers with a heuristic monitor on TCP flows

We propose adaptive proportional (P) and proportional‐integral (PI) controllers for Active Queue Management (AQM) in the Internet. We apply the classical control theory in the controller design and choose a proper phase margin to achieve good performance of AQM. We have identified a simple heuristic parameter that can monitor the changes of network environment. Our adaptive controllers would self‐tune only when the dramatic change in the network parameters drift the monitoring parameter outside its specified interval. When compared to P controller, a PI controller has the advantage of regulating the TCP source window size by adjusting the packet drop probability based on the knowledge of instantaneous queue size, thus steadying the queue size around a target buffer occupancy. We have verified our controllers by OPNET simulation, and shown that with an adaptive PI controller applied, the network is asymptotically stable with good robustness. Copyright © 2005 John Wiley & Sons, Ltd.     

On designing self-tuning controllers for AQM routers supporting TCP flows based on pole placement

This paper revisits the simple pole placement technique in the classical control theory, and exploits this technique to propose two kinds of controllers for active queue management (AQM) in Internet protocol (IP) routers: the self-tuning proportional controller based on pole placement (ST/spl I.bar/P/spl I.bar/PP) and the self-tuning proportional-plus-integral controller based on pole placement (ST/spl I.bar/PI/spl I.bar/PP). The damping ratio /spl xi/ and undamped natural frequency /spl omega//sub n/ can be appropriately chosen such that: 1) the transient response performance of the system is satisfied and 2) all the poles would lie in the left-half s-plane to guarantee the stability of the control system. The self-tuning controllers can assign proper intervals of /spl xi/ and /spl omega//sub n/ to achieve good AQM performance and thereby adapting the system to significant load changes very well. Furthermore, the ST/spl I.bar/PI/spl I.bar/PP controller can regulate the packet drop probability based on the knowledge of the instantaneous queue size, and clamp the steady value of the queue length to a specified reference value. We verify the effectiveness of these two controllers via OPNET simulation. Our simulation results show the following: 1) choosing appropriate /spl xi/ and /spl omega//sub n/ can successfully satisfy the transient response of the system and 2) when the network load changes, the ST/spl I.bar/P/spl I.bar/PP controller and the ST/spl I.bar/PI/spl I.bar/PP controller exhibit extremely short settling time.     

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 methodology is described and the results of the comparison with random early detection (RED), tail drop, and PI controller are presented.     

A compensated PID active queue management controller using an improved queue dynamic model

Beside the major objective of providing congestion control, achieving predictable queuing delay, maximizing link utilization, and robustness are the main objectives of an active queue management (AQM) controller. This paper proposes an improved queue dynamic model while incorporating the packet drop probability as well. By applying the improved model, a new compensated PID AQM controller is developed for Transmission Control Protocol/Internet Protocol (TCP/IP) networks. The non‐minimum phase characteristic caused by Padé approximation of the network delay restricts the direct application of control methods because of the unstable internal dynamics. In this paper, a parameter‐varying dynamic compensator, which operates on tracking error and internal dynamics, is proposed to not only capture the unstable internal dynamics but also reduce the effect of uncertainties by unresponsive flows. The proposed dynamic compensator is then used to design a PID AQM controller whose gains are obtained directly from the state‐space representation of the system with no further gain tuning requirements. The packet‐level simulations using network simulator (ns2) show the outperformance of the developed controller for both queuing delay stability and resource utilization. The improved underlying model leads also to the faster response of the controller. Copyright © 2013 John Wiley & Sons, Ltd.     

Advances in Active Queue Management (AQM) Based TCP Congestion Control

Current end-to-end Internet congestion control under tail-drop (TD) queue management experiences performance degradations such as multiple packet losses, high queueing delay and low link utilization. In this paper, we review recently proposed active queue management (AQM) algorithms for supporting end-to-end transmission control protocol (TCP) congestion control. We focus recently developed control theoretic design and analysis method for the AQM based TCP congestion control dynamics. In this context, we analyze the problems of existing AQM proposals in which congestion is detected and controlled reactively based on current and/or past congestion. Then we argue that AQM based TCP congestion control should be adaptive to the dynamically changing traffic situation in order to detect, control and avoid the current and the incipient congestion proactively. Finally, we survey two adaptive and proactive AQM algorithms, PID-controller and Pro-Active Queue Management (PAQM), designed using classical proportional-integral–derivative (PID) feedback control to overcome the reactive congestion control dynamics of existing AQM algorithms. A comparative study of these AQM algorithms with existing AQM algorithms is given. A simulation study under a wide range of realistic traffic conditions suggests that PID-controller and PAQM outperform other AQM algorithms such as random early detection (RED) [Floyd and Jacobson, 18] and proportional-integral (PI) controller [Hollot et al., 24].     

Rate‐based proportional–integral control scheme for active queue management

Most high‐speed links do not have adequate buffering and as a result Active Queue Management (AQM) schemes that utilize queue size information for congestion control cannot be effectively applied on these links. A high‐speed link will, typically, have small buffers in relation to the bandwidth‐delay product of the link. In this paper we argue that rate‐based AQM schemes be used for such links. The goal here is to match the aggregate rate of the active TCP connections to the available capacity while maintaining minimal queue size and high link utilization. The AQM scheme described here employs a Proportional–Integral (PI) control strategy and explicitly takes into account the time delay in the control process. Copyright © 2006 John Wiley & Sons, Ltd.     

AQM controller design for TCP networks based on a new control strategy

When the network suffers from congestion, the core or edge routers signal the incidence of congestion through the active queue management (AQM) to the sources. The time-varying nature of the network dynamics and the complex process of retuning the current AQM algorithms for different operating points necessitate the development of a new AQM algorithm. Since the non-minimum phase characteristics of the network dynamics restrict direct application of the proportional-integral-derivative (PID) controller, we propose a compensated PID controller based on a new control strategy addressing the phase-lag and restrictions caused by the delay. Based on the unstable internal dynamics caused by the non-minimum phase characteristics, a dynamic compensator is designed and a PID controller is then allowed to meet the desired performance objectives by specifying appropriate dynamics for the tracking error. Since the controller gains are obtained directly from the dynamic model, the designed controller does not require to be tuned over the system operating envelop. Moreover, simulation results using ns2 show improvements over previous works especially when the range of variation of delay and model parameters are drastic. Simplicity, low computational cost, self-tuning structure and yet considerable improvement in performance are exclusive features of the proposed AQM for the edge or core routers.     

A stochastic dynamic controller for random early detection queues using a Kalman filter algorithm

The stabilizing random early detection (RED) congestion control algorithm in transmission control protocol (TCP)/IP networks is a control theory problem. Significant attention has been drawn to this problem in the networking and control theory research communities. In this paper, we use a nonlinear dynamic model of the TCP RED congestion control algorithm to analyze and design active queue management (AQM) control systems. A linearized model of RED behavior around its nominal operating point which implicitly includes the delay in the control signal is derived. It is assumed that the system model is corrupted at the input and output by zero mean white Gaussian noise signals. An optimal state feedback stochastic controller is designed for the linearized model of the system in conjunction with a Kalman filter for state estimation. To illustrate the proposed design methodology, simulations results are presented and discussed. The proposed stochastic controller is applied to the nonlinear model of the system; Simulation results indicate that the proposed controller keeps the queue length bounded in an appropriate stochastic sense. Copyright © 2009 John Wiley & Sons, Ltd.     

基于粒子群优化的网络拥塞控制新算法

PI控制器常用于主动队列管理中,但参数整定上的试凑法具有盲目性,算法的瞬态性能也不够理想.本文推导了基于流体流理论的网络简化模型,基于该模型将集群智能中的改进粒子群优化算法(PSO)应用于PID控制器参数优化,定义了一个综合调节时间、上升时间、超调量、系统静态误差、正弦跟踪误差等动静态性能指标函数,在给定的参数空间进行组合优化搜索,迅速求得获取使性能指标优化函数极小化的一组PID控制器参数,将PID控制器应用于网络主动队列管理系统中.仿真结果表明,在大时滞和突发业务流的冲击两种情况下,该方法设计的控制器的动静态性能优于RED、PI算法,超调量均小于5%,调节时间分别小于5秒、4秒,稳态误差分别小于两个数据包和3个数据包.     

基于H∞控制理论的网络拥塞控制器的设计

针对具有多维性、非线性、动态性、不确定性等复杂特征的计算机网络系统,文章从控制理论出发,提出了一种基于H∞控制理论的主动队列管理（AQM）算法,文章着重分析RED算法。首先,建立了AQM／TCP拥塞控制的动态模型;其次,系统的渐进稳定由线性矩阵不等式（LMI）描述,并应用MATLAB的LMI工具箱求解H∞控制的一般线性时滞系统;然后将求解结果应用到RED中,从而得出了控制器。最后在NS2平台上进行了仿真实验,试验结果表明,该算法在解决系统不确定性引起的鲁棒性问题上是有效的。     

主动队列管理中的PID控制器

作为对终端系统上拥塞控制的一种补充,中间节点上的主动队列管理(AQM)策略在保证较高吞吐量的基础上有效地控制队列长度,从而实现了控制端到端的时延,保证QoS的目的。C.Hollot等人(2001)用经典控制理论中频域校正的方法设计了用于AQM的PI控制器,但参数整定上的试凑方法不免代有盲目性;算法的瞬态性能指标也不够理想。为此,该文引入了微分环节来增强系统的响应能力,同时给出了基于稳定裕度的参数整定方法,使PID控制器的稳定性有了绝对保障。仿真试验表明PID算法的调节时间远远短于PI控制器,从而为在负载瞬息万变的网络环境中实现控制分组排队等待时间的目标提供了有力的技术保障。     

Advances in internet congestion control

In this survey, we first review the concept of congestion control with a focus on the Transmission Control Protocol⁄Internet Protocol (TCP⁄IP). We describe many recently proposed algorithms to combat congestion and improve performance, particularly active queue management (AQM) algorithms such as random early detection (RED) and its variants. We then survey control-theoretic analysis and design of TCP congestion control with an AQM scheme. In addition, we discuss three problems associated with AQM proposals: parameter setting, the insensitivity to the input traffic load variation, and the mismatch between macroscopic and microscopic behavior of queue length dynamics. As alternatives to AQM algorithms, we also survey architectural approaches such as modification of source or network algorithms, and economic approaches including pricing or optimization of allocated resources. Finally, we list many open issues that persist in the design, operation, and control of the Internet.     

A novel adaptive traffic prediction AQM algorithm

In the Internet, network congestion is becoming an intractable problem. Congestion results in longer delay, drastic jitter and excessive packet losses. As a result, quality of service (QoS) of networks deteriorates, and then the quality of experience (QoE) perceived by end users will not be satisfied. As a powerful supplement of transport layer (i.e. TCP) congestion control, active queue management (AQM) compensates the deficiency of TCP in congestion control. In this paper, a novel adaptive traffic prediction AQM (ATPAQM) algorithm is proposed. ATPAQM operates in two granularities. In coarse granularity, on one hand, it adopts an improved Kalman filtering model to predict traffic; on the other hand, it calculates average packet loss ratio (PLR) every prediction interval. In fine granularity, upon receiving a packet, it regulates packet dropping probability according to the calculated average PLR. Simulation results show that ATPAQM algorithm outperforms other algorithms in queue stability, packet loss ratio and link utilization.     

基于动态矩阵控制的主动队列管理算法

针对Internet系统,通过对流体流模型的分析,提出了一个新的预测模型.该模型形式简单,参数的计算相对容易,并且能根据当前的网络情况有效的预测拥塞窗口的变化.结合动态矩阵控制 (Dynamic Matrix Control,DMC) 理论,提出了一种新的主动队列管理算法——DMCAQM 算法,给出了DMCAQM 的详细设计过程,稳定性分析和参数选取原则.大量不同网络环境的仿真实验表明DMCAQM 算法是有效的.与PI、RaQ 和REM 等算法相比较,DMCAQM 有收敛速度快、队列抖动小的优点.同时,由于DMCAQM 的采样间隔相对较大,而算法实现简单,所以计算量小,占用的路由器资源更少.     

Adaptive fuzzy sliding mode active queue management algorithms

Active queue management (AQM) is aimed at achieving the tradeoff between link utilization and queuing delay to enhance TCP congestion control and is expected to perform well for a wider-range of network conditions. Static AQM schemes despite their simplicity, often suffer from long response time due to conservative parameter setting to ensure stability. Adaptive parameter settings, which might solve this problem, remain difficult from implementation point of view. In this paper, we propose an adaptive fuzzy sliding mode (AFSM) AQM algorithm to achieve fast response and yet good robustness. The AFSM algorithm uses the queue length and its differential as the input of AQM and adjusts fuzzy rules by the measurement of packet loss ratio dynamically. The stability analysis under heterogeneous round trip times provides guidelines for parameter settings in AFSM and guarantees that the stability of AFSM is independent of the active TCP flows. This merit as well as other performances is examined under various network environments. Compared to some typical AQMs, the AFSM algorithm trades off the throughput with queuing delay better and achieves a higher per-flow throughput. Finally, AFSM can be executed at a scale of seconds with the least fuzzy rules.     

几种主动式队列管理算法的比较研究

主动式队列管理(Active Queue Management,AQM)技术是IETF为了解决Internet拥塞控制问题而提出的一种路由器缓存管理技术.本文对几种主要AQM算法RED、BLUE、ARED和SRED的性能在基于ns-2仿真实验的基础上进行了比较研究.研究的性能包括队列长度、丢包概率、丢包率、连接数对吞吐量的影响及缓冲区大小对链路利用率的影响等.仿真结果表明BLUE、ARED和SRED在这几方面的性能都要优于RED算法.     

主动队列管理算法性能评价：比较研究

对当前的主动队列管理算法进行了分类，然后基于NS2网络仿真器比较了它们在不同流量和网络拓扑条件下的多种性能指标。主要结论包括：ARED综合表现最好；PI和REM的瞬态性能较差，对动态流量响应较慢：REM和没有ECN支持的AVQ可以得到较小的时延，但同时牺牲了链路的带宽利用率并造成大量分组丢失；在多瓶颈网络拓扑中，大部分算法的性能有所提高。     

Active queue management algorithm based on data-driven predictive control

Model predictive control (MPC) is a popular strategy for active queue management (AQM) that is able to incorporate physical and user defined constraints. However, the current MPC methods rely on explicit fluid model of TCP behavior with input time delay. In this paper, we propose a novel AQM algorithm based on data-driven predictive control, called Data-AQM. For Internet system with large delay, complex change and bad disturbance, data-driven predictive controller can be obtained directly based on the input–output data alone and does not require any explicit model of the system. According to the input–output data, the future queue length in data buffer, which is the basis of optimizing drop probability, is predicted. Furthermore, considering system constraints, the control requirement is converted to the optimal control objective, then the drop probability is obtained by solving the optimal problem online. Finally, the performances of Data-AQM are evaluated through a series of simulations.     

A novel Markov analytical model for the TCP/AQM systems

A novel closed-loop feedback TCP/AQM(Transfer Control Protocol/Active Queue Management) model is proposed in this paper using a discrete-time Markov chain,and a way to calculate the equilibrium distribution of this model is given.In the model,system time is divided into time slots,the bottleneck router queue model and TCP window size model in each slot are analyzed.Finally,by combining adjacent slots,an integrated TCP/AQM analytical model is developed.By this model,the average values of packets dropping rat...     

Modeling and Analysis of Active Queue Management Schemes under Bursty Traffic

Traffic congestion arising from the shared nature of uplink channels in wireless networks can cause serious problems for the provision of QoS to various services. One approach to overcome these problems is to implement some effective congestion control mechanisms at the downlink buffer at the mobile network link layer or at gateways on the behalf of wireless network access points. Active queue management (AQM) is an effective mechanism to support end-to-end traffic congestion control in modern high-speed networks. Initially developed for Internet routers, AQM is now being also considered as an effective congestion control mechanism to enhance TCP performance over 3G links. This paper proposes an analytical performance model for AQM using various dropping functions. The selection of different dropping functions and threshold values required for this scheme plays a critical role on its effectiveness. The model uses a well-known Markov-modulated Poisson process (MMPP) to capture traffic burstiness and correlations. The validity of the model has been demonstrated through simulation experiments. Extensive analytical results have indicated that exponential dropping function is a good choice for AQM to support efficient congestion control.