TCPV egas／AQM系统稳定性分析与算法设计

本文建立支持TCP Vegas的AQM控制器设计的非线性时滞微分模型。通过对该模型线性化,可以得到以丢包率和瓶颈路由器队列长度为输入输出的TCP Vegas／AQM系统的小信号模型。我们采用劳斯判据,设计了满足闭环系统稳定性的PI型AQM控制器。仿真结果显示了所提方法的有效性。     

Adaptive generalized minimum variance congestion controller for dynamic TCP/AQM networks

Generic generalized minimum variance-based (GMV) controllers have been adopted as efficient control mechanisms especially in presence of measurement noise. However, such controllers exhibit degraded performance with change in process dynamics. To overcome this problem, a novel congestion controller based on active queue management (AQM) strategy for dynamically varying TCP/AQM networks known as adaptive generalized minimum variance (AGMV) is proposed. AGMV is the combination of the real-time parameter estimation and GMV. The performance of the proposed scheme is evaluated and compared with its adaptive minimum variance (AMV) counterpart under two distinct scenarios: TCP network with unknown parameters and TCP network with time varying parameters. Simulation results indicate that, in either case, AGMV is able to keep the queue length around the desired point. In addition, the superior performance of the proposed controller has been shown with regard to the PI controller, which is well-known in the AQM domain.     

高速TCP/AQM中的RED算法分析

通过建立适用于高速TCP和AQM反馈控制系统的流体流模型,分析高速TCP/AQM闭环系统的稳定性。采用频域稳定裕度,得到高速TCP/AQM中RED算法的稳定参数区域。基于MATLAB/SIMULINK的仿真结果验证了该方法的有效性。     

Computing non-fragile PI controllers for delay models of TCP/AQM networks

This article focuses on the stabilisation problem of fluid-flow delay models of transmission control protocol/active queue management (TCP/AQM) networks by using a proportional-integral (PI) controller as AQM strategy. More precisely, the complete set of PI controllers that exponentially stabilises the corresponding linear time-delay system is derived. Using the particular geometric properties of this set of the controller parameters, the issues of robustness to uncertainty in the network parameters and to perturbation in the controller coefficients are addressed. Then, a methodology to compute a non-fragile PI AQM controller is provided. Finally, exponential estimates for the closed-loop system solutions, allowing to evaluate the performance of the corresponding PI-controlled closed-loop system, are proposed by using a Lyapunov–Krasovskii functional approach. An illustrative example completes the presentation.     

Research for AQM based on MiniMax method

This paper proposes an active queue management (AQM) controller for a class of linearized congestion router network systems in the presence of unknown time-varying link number and disturbances. Based on the idea of MiniMax method in game theory, a novel output feedback controller is specially designed with the improved robustness to the disturbances and parameter variations. By applying the proposed algorithm in the terms of LMIs, the worst effect caused by the disturbance can be evaluated using MiniMax method, and mean while the controller is optimally designed to deal with the system under the worst condition. Finally, the effectiveness of presented AQM method is verified on the software platform of NS2.     

自适应的PIP主动队列管理机制

近年来AQM的研究者提出了多种主动队列管理机制,包括RED,PI,REM,AVQ,PD,SMVS,PIP等,它们之间的主要区别在于丢弃概率的计算方法不同,其中基于反馈校正的PIP是综合性能更为突出的一种算法,但是遗憾的是其参数不能实现自动配置 .结合单神经元自适应PID控制器,为PIP算法建立了自适应的模型,提出一种参数自适应的PIP算法 .通过NS2仿真实验,验证了该算法能提高链路利用率和降低报文丢失率,有效缓解了根据特定网络条件配置算法参数的问题 .结合PI,REM,AVQ,PD等AQM算法,讨论了该自适应模型在其他AQM机制中的推广 .     

单神经元自适应PID控制器在AQM中的应用

主动队列管理(AQM)对于保持TCP网络高性能是一种有效的策略。AQM的基本机制是调节数据包进入路由器缓冲区的速率,从而避免网络拥塞。针对传统PID控制器在拥塞控制过程中参数固定的缺点,将神经网络理论引入AQM的研究中,设计了一种改进的单神经元自适应PID主动队列管理器。基于NS2平台的仿真结果表明,与PID控制器及传统的单神经元自适应PID控制器相比,改进的控制器对网络环境的变化有更强的适应能力和更好的稳定性。     

主动队列管理中的APD和APID控制器的设计*

AQM策略作为终端系统上网络拥塞控制的一种补充,能在保证较高吞吐量的基础上有效地控制队列长度,从而实现控制端到端的时延,保证QoS。理论上,很多AQM机制可以最终归结为PID控制器。因此在研究PD和PID控制器模型的基础上,设计了两种新的适应性控制机制,即APD和APID控制器,使系统在网络变化的情况下能提高其稳定性和网络性能,并仿真验证了这两种新算法的稳定性和网络性能。     

基于单神经元预测PID的主动队列管理算法

针对网络中普遍存在的大时滞现象以及网络参数实时变化问题,将单神经元PID预测控制器用于主动队列管理算法(AQM).利用单神经元的自学习能力解决网络实时变化时算法参数的在线整定问题,并利用Levinson预测器有效地解决了大时滞对网络性能的影响,最后通过仿真进一步验证了提出算法的有效性.     

Tuning of Gaussian stochastic control systems

A closed-loop system consisting of a control system and an adaptive controller is called tuning for a specified control objective if the real system and the ideal system defined below achieve the same value for the control objective. The real system is the system consisting of the unknown control system in closed loop with the adaptive controller in which the parameters of the adaptive controller have been determined by identification under feedback or in closed loop. The ideal system is the system consisting of the unknown control system in closed loop with a controller in which the controller has been synthesized with knowledge of the unknown control system and such that the closed-loop system satisfies the control objective. Both the Gaussian stochastic control system with full observations and with partial observations are considered. The approach to the problem is based on stochastic realization theory for Gaussian systems. The control objectives of minimum variance control and pole placement are also given. Necessary conditions for tuning are discussed     

大时滞网络自适应主动队列管理新算法

针对PID控制器无法严格处理主动队列管理（AQM）中的大时滞情况,且不能随着变化的网络环境在线调节参数,提出了一种基于增益自适应Smith预估控制和模糊控制的大时滞网络的自适应PID主动队列管理（GAS-FPID）算法。引入增益自适应Smith预估控制器实现滞后补偿,模糊控制器来实现PID参数动态网络环境的在线调整;NS2仿真表明,所提出算法能克服滞后的影响,能快速的适应动态网络环境,具有很好的稳定性和鲁棒性。     

TCP/AQM系统大时间尺度模型

网络传输连接的往返时延(round-trip times,RTT)大小各不相同,因此TCP/AQM系统本质为一多时滞回路耦合系统.由于RTT分布范围远大于控制量调节周期,这给准确评估控制效果带来很大困难.已有基于控制理论的主动队列管理(active queue management,AQM)算法多以流体流模型为基础进行设计,没有充分考虑RTT和采样周期对系统性能的影响.对于TCP/AQM系统,合理的评价方法是对调节过程进行评价,而非仅评价单个采样周期内的控制量是否合适.本文结合数据驱动控制思想和系统自身特征,统一从路由视角对TCP与AQM之间的交互进行抽象,通过时间扩展从更大的时间尺度去评价控制量调节过程,然后基于此模型设计自适应AQM算法–—大时间尺度AQM算法(large time scale AQM,LTSAQM).仿真结果表明,该算法收敛速度快,排队时延抖动小,特别是在长时滞网络环境下,性能明显改善.     

NFL:一种基于活动流参数估计的自适应模糊AQM算法

针对主动队列管理（AQM）机制面对动态突变的网络存在参数配置难问题,提出一种将模糊AQM和活动流参数估计策略相结合的白适应AQM算法（NFL）．在综合权衡各性能指标的基础上,设计了一组能适应一定网络变化的模糊规则,并对算法进行了运算优化．为捕获网络突发流,引入了一种基于Bloom滤波器的无状态维护活动流参数估计策略,并依此提出一个模糊AQM输出增益补偿器．实验结果表明,NFL能较好地适应网络变化,相对其他算法,具有更快的收敛速度和稳定的稳态队列控制性能．     

A robust fractional-order PID controller design based on active queue management for TCP network

In this paper, a robust fractional-order controller is designed to control the congestion in transmission control protocol (TCP) networks with time-varying parameters. Fractional controllers can increase the stability and robustness. Regardless of advantages of fractional controllers, they are still not common in congestion control in TCP networks. The network parameters are time-varying, so the robust stability is important in congestion controller design. Therefore, we focused on the robust controller design. The fractional PID controller is developed based on active queue management (AQM). D-partition technique is used. The most important property of designed controller is the robustness to the time-varying parameters of the TCP network. The vertex quasi-polynomials of the closed-loop characteristic equation are obtained, and the stability boundaries are calculated for each vertex quasi-polynomial. The intersection of all stability regions is insensitive to network parameter variations, and results in robust stability of TCP/AQM system. NS-2 simulations show that the proposed algorithm provides a stable queue length. Moreover, simulations show smaller oscillations of the queue length and less packet drop probability for FPID compared to PI and PID controllers. We can conclude from NS-2 simulations that the average packet loss probability variations are negligible when the network parameters change.     

Characteristic model based adaptive controller design and analysis for a class of SISO systems一类SISO系统基于特征模型的极点配置自适应控制设计与分析

The design of an adaptive controller and stability analysis of the corresponding closed loop system are discussed for a class of SISO systems based on the characteristic model method. The obtained characteristic model is a second-order slow time-varying linear system with a compress mapping function for the system modeling error. The pole placement method is used to design the controller, and sufficient conditions for the stability of the closed loop system are obtained based on the robust control theory of slow time-varying systems with perturbations. The effectiveness of the proposed method is illustrated by two numerical examples.     

Stable Queue Management in communication networks

Since Active Queue Management (AQM) was recommended by the Internet Engineering Task Force (IETF) as an efficient way to overcome performance limitations of Transmission Control Protocol (TCP), several studies have proven control theory to be a promising field for the design and analysis of congestion control in homogenous communication networks. AQM is gaining increased importance due to reports of buffer-induced latencies throughout the Internet. The increasing volume and diversity of traffic types (i.e., data, voice, and video) suggests that traffic management mechanisms, in general, and AQM schemes, specifically, must not only focus on the critical issue of congestion control but must also consider the QoS demands of heterogeneous traffic. However, to combine quality-of-service provisioning with congestion control, AQM design needs to be reconsidered. In this paper, we propose a state feedback controller design scheme for heterogeneous networks preserving the closed-loop system stability. Delay dependant stability conditions of the closed loop system are derived based on the Lyapunov-Krasovskii method. The proposed approach offers flexible choice of control parameters allowing the network administrator to control fairness and response time for each individual source node in a network of multiple links with different delay properties. The performance and robustness of the proposed controller were illustrated and analyzed using event-based computer simulations.     

基于模糊推理的鲁棒主动队列管理算法

基于常规控制理论的主动队列管理(AQM)算法在复杂动态网络环境下对参数变化比较敏感,难以保证队列稳定性且缺乏鲁棒性。针对上述问题提出基于队列长度和链路速率相对变化率的模糊AQM算法,以队列长度与期望队列长度以及链路速率与链路容量的相对误差量作为网络拥塞指示,采用模糊推理得出中间节点的丢包概率。仿真实验表明,该算法具有良好的队列稳定性和较小的队列延时,对网络的非线性和负载波动等不确定因素具有鲁棒性。     

Robust discrete adaptive input-output-based sliding mode controller

A robust input-output-based discrete adaptive sliding mode controller is proposed. It combines an integral action, a nonlinear output feedback, an adjustable sliding mode and an adaptive plant parameter estimator. The controller design is carried out via the Lyapunov direct method. A pole assignment procedure is developed for determination of the integral control gain and the coefficients of the sliding mode hyperplane. An on-line update for coefficients of the hyperplane is used to improve control loop behaviour further. Compared with the optimally tuned proportional-integral-derivative (PID) controller, the new controller has increased robustness with regard to the variation in the main process parameters and it has much better set point tracking characteristics. The new controller also exhibits very good disturbance rejection property comparable work or better than to that obtained by the optimally tuned PID controller. Simulation experiments are made to illustrate the quality and robustness of control achieved.     

基于D稳定域和ITAE准则的主动队列管理算法

主动队列管理(active queue management,简称AQM)是网络拥塞控制的研究热点之一,其中的关键问题是如何设计反馈控制策略.提出一种新的基于D稳定域和时间乘以误差绝对值乘积积分(integral of time-weighted absolute error,简称ITAE)性能准则的比例-积分-微分(proportional-integral-differential,简称PID)优化设计方法(简称DITAE-PID),并用于AQM控制器的设计,控制闭环系统的理想动态性能.首先在复平面上设定一组理想的D稳定域,然后以ITAE为目标函数,通过数值优化算法求出控制器的参数,使得闭环系统的所有特征根都在D稳定域内,以降低排队延时,提高有效吞吐量.对比仿真实验结果表明,该算法能够预先探测和控制拥塞,有较好的鲁棒性,链路利用率更高,丢包率更小,平均队列长度更趋于期望值,同时,趋于期望队列长度的时间更短,其综合性能明显优于典型的随机早期探测(random early detection,简称RED)和比例-积分(proportional-integral,简称PI)算法.     

不确定时滞TCP 网络中基于T-S 模型的滑模AQM算法

针对传输控制协议(TCP)网络中的拥塞控制问题,基于T-S模糊模型,提出一种滑模主动队列管理(AQM)算法.考虑到TCP网络中存在的不确定和时变时滞因素,对非线性TCP网络进行了T-S模糊模型的建模.利用LMI设计了一个渐近稳定的滑模面,并提出一种能更好抑制抖振现象的到达条件,基于该到达条件设计的控制器能有效地抑制路由器中队列长度的振荡.大量仿真结果表明,所提出的算法比普通滑模AQM算法具有更好的稳定性和鲁棒性.