A novel self-tuning feedback controller for active queue management supporting TCP flows

Wireless access points act as bridges between wireless and wired networks. Since the actually available bandwidth in wireless networks is much smaller than that in wired networks, there is a bandwidth disparity in channel capacity which makes the access point a significant network congestion point. The recently proposed active queue management (AQM) is an effective method used in wired network and wired-wireless network routers for congestion control, and to achieve a tradeoff between channel utilization and delay. The de facto standard, the random early detection (RED) AQM scheme, and most of its variants use average queue length as a congestion indicator to trigger packet dropping. In this paper, we propose a Novel autonomous Proportional and Differential RED algorithm, called NPD-RED, as an extension of RED. NPD-RED is based on a self-tuning feedback proportional and differential controller, which not only considers the instantaneous queue length at the current time point, but also takes into consideration the ratio of the current differential error signal to the buffer size. Furthermore, we give theoretical analysis of the system stability and give guidelines for the selection of feedback gains for the TCP/RED system to stabilize the instantaneous queue length at a desirable level. Extensive simulations have been conducted with ns2. The simulation results have demonstrated that the proposed NPD-RED algorithm outperforms the existing AQM schemes in terms of average queue length, average throughput, and stability.     

主动队列管理RED算法改进与实验仿真研究

分析了RED及其改进算法的原理和局限性,提出了一种非线性高阶RED拥塞控制机制。该算法利用一个高阶分组丢弃函数,在下限阈值附近以较低的概率标记丢弃分组,在上限阈值附近迅速提高分组的标记丢弃概率。并对网络仿真器NS2进行扩展,通过系列仿真实验验证了改进算法有效提高了网络性能。     

Internet路由器的AQM策略的研究与分析

分析了几种典型及最新提出的AQM策略算法,并比较了各种策略算法的优缺点,同时对AQM的拥塞指示方式进行了分析,最后给出了几种AQM策略的实验分析结果。     

主动队列管理算法比较研究

本文对FRED、CHOKe、CSFQ、AFD等几个主动队列管理算法进行了对比研究,并且结合实验结果对算法中存在的问题及其原因进行了深入的分析,并对算法的改进提出了一些建议,希望能为今后的工作提供一定的支持。     

A novel numerical algorithm based on self-tuning controller to support TCP flows

Active queue management (AQM) is an effective method used in Internet routers for congestion control, and to achieve a trade off between link utilization and delay. The de facto standard, the random early detection (RED) AQM scheme, and most of its variants use average queue length as a congestion indicator to trigger packet dropping.     

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.     

Nonlinear RED: A simple yet efficient active queue management scheme

Among various active queue management schemes (AQM), random early detection (RED) is probably the most extensively studied. Unlike the existing RED enhancement schemes, we replace the linear packet dropping function in RED by a judicially designed nonlinear quadratic function. The rest of the original RED remains unchanged. We call this new scheme Nonlinear RED, or NLRED. The underlying idea is that, with the proposed nonlinear packet dropping function, packet dropping becomes gentler than RED at light traffic load but more aggressive at heavy load. As a result, at light traffic load, NLRED encourages the router to operate in a range of average queue sizes rather than a fixed one. When the load is heavy and the average queue size approaches the pre-determined maximum threshold (i.e. the queue size may soon get out of control), NLRED allows more aggressive packet dropping to back off from it. Simulations demonstrate that NLRED achieves a higher and more stable throughput than RED and REM, another efficient variant of RED. Since NLRED is fully compatible with RED, we can easily upgrade/replace the existing RED implementations by NLRED.     

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。     

基于高层模糊变结构控制的主动队列管理算法

从控制论的角度出发,主动队列管理算法将IP层纳入到拥塞控制机制.该文根据TCP拥塞控制机制的线性化模型,利用线性化模型时延因子的多项式表达式,提出了基于高层模糊变结构控制主动队列管理算法,简化了控制器的设计.NS仿真结果显示本算法提高了拥塞控制的性能和鲁棒性,有效地补偿了时延因子对于控制性能的影响.     

不确定输入延时网络系统的鲁棒拥塞控制

基于滑模控制（SMC）设计了一种主动队列管理（AQM）算法,该算法可保证具有有界的不确定输入延时网络系统渐进稳定.引入一种状态变换来消除延时的影响,通过Lyapunov稳定性分析,给出了保证系统渐进稳定的最大允许的延时边界.仿真结果表明,该方法可以获得良好的暂态和稳态响应,在网络条件变化的情况下,该算法优于传统的PI控制和滑模控制.     

A framework to determine bounds of maximum loss rate parameter of RED queue for next generation routers

Random early detection (RED) is expected to eliminate global synchronization by random active packet drop. Its packet drop probability is decided by the maximum packet drop probability in its drop function, buffer thresholds, and average queue length. It has been observed that for a large number of connections, a small value of the maximum packet drop probability may not eliminate global synchronization. Furthermore, since RED uses four parameters to regulate its performance, it is necessary to relate its maximum drop probability with those parameters. The objective of this paper is to develop a framework for the bounds of the maximum drop probability of RED, based on TCP channel model and traffic characteristics. The value of the maximum drop probability obtained by our model will make RED queue achieve its targeted goals.     

A linear system analysis of RED

The random early detection (RED) algorithm proposed by Floyd and Jacobson [IEEE/ACM Trans. Networking 1 (4) (1993) 397] is a simple and quite effective mechanism for active queue management and as a result has been widely implemented in Internet routers. While RED certainly performs better than drop-tail, its parameters are difficult to tune to give good performance under different congestion scenarios. Also, studies have shown that RED does not stabilize the queue lengths in routers, because its equilibrium queue length strongly depends on the number of active TCP connections. As a result numerous variants of RED have been proposed to work around the performance problems of RED. In this paper, using inferences drawn from a linear systems analysis, we provide an insight into why RED is difficult to tune. The same linear systems analysis is used to show that the DRED algorithm proposed in [Computer 36 (2–3) (2001) 203; Comput. Commun. 24 (12) 2001 1170] overcomes the performance limitations of RED [IEEE/ACM Trans. Network. 1 (4) (1993) 397].     

具有最小平方误差积分的主动队列管理算法ISE-GPM-PID

随着互联网流媒体应用的增多,流媒体流量在互联网总流量中所占比例越来越大。流媒体流量具有时延敏感和容忍丢包等特点,通常采用UDP协议传输;UDP流量是对TCP/AQM模型的干扰流量,但现有针对TCP长流设计的主动队列管理算法缺乏抗击UDP流量干扰的能力,不能适应互联网视频和音频流量日益增多的局面。利用TCP/AQM模型,设计了一个具有最小平方误差积分,且相角裕度在30°至60°之间,幅值裕度在2至5之间的基于PID控制器的主动队列管理算法ISE-GPM-PID。该算法对UDP流量具有良好的抗干扰能力,能适应互联网流媒体和Web应用日益增多的局面;同时其响应速度快,计算开销小,能用于大时滞网络环境,且鲁棒性好。     

几种主动队列管理算法的仿真及性能评估

采用仿真分析的方法,系统地研究了当前提出的用于Internet路由器缓冲管理的一系列主动队列管理(AQM)算法的性能。根据AQM的设计原理,将当前的AQM算法划分为3类：基于队列长度,基于网络负载和同时基于队列长度和网络负载的AQM算法。仿真研究和分析表明,现有的AQM算法不能适应网络流量的动态变化。     

Stability of TCP/RED systems in AQM routers

By applying the time-delay control theory to a TCP/RED dynamic model, this note establishes some explicit conditions under which the TCP/RED system is stable in terms of the average queue length. Then, the stability region is discussed. Finally, the results are illustrated by using ns2 simulations, which demonstrates that it is able to choose an appropriate control parameter max/sub p/ of RED based on the stability conditions derived in this note, to achieve satisfactory network performance. It is found, by comparison, that this improved performance is better than that of three other typical active queue management (AQM) schemes-the random exponential marking (REM), proportional-integral (PI) controller, and adaptive virtual queue (AVQ) schemes.     

基于路由队列资源自适应的非线性随机早期检测算法

针对随机早期检测(RED)算法在网络拥塞控制中的缺点和复杂性,提出了基于路由队列资源(缓冲)自适应的新算法(ND-RED)。该算法采用非线性丢包策略和动态调整算法参数的方法,使得路由队列长度稳定在参考值附近,从而有效控制了网络拥塞,高效地利用了资源。最后实验结果表明,ND-RED算法具有良好的稳定性,在队列控制和丢包率控制方面优于RED算法。     

Managing Internet routers congested links with a Kohonen-RED queue

The behaviour of the TCP AIMD algorithm is known to cause queue length oscillations when congestion occurs at a router output link. Indeed, due to these queueing variations, end-to-end applications experience large delay jitter. Many studies have proposed efficient active queue management (AQM) mechanisms in order to reduce queue oscillations and stabilize the queue length. These AQM attempt to improve the random early detection (RED) model. Unfortunately, these enhancements do not react in a similar manner for various network conditions and are strongly sensitive to their initial setting parameters. Although this paper proposes a solution to overcome the difficulties of configuring the RED parameters by using a Kohonen neural network model; another goal of this study is to investigate whether cognitive intelligence could be placed in the core network to solve such stability problem. In our context, we use results from the neural network area to demonstrate that our proposal, named Kohonen-RED (KRED), enables a stable queue length without complex parameters setting or passive measurements to obtain a correct configuration.     

Active queue management via event-driven feedback control

Active queue management (AQM) is investigated to avoid incipient congestion in gateways to complement congestion control run by the transport layer protocol such as the TCP. Most existing work on AQM can be categorized as (1) ad-hoc event-driven control and (2) time-driven feedback control approaches based on control theory. Ad hoc event-driven approaches for congestion control, such as RED (random early detection), lack a mathematical model. Thus, it is hard to analyze their dynamics and tune the parameters. Time-driven control theoretic approaches based on solid mathematical models have drawbacks too. As they sample the queue length and run AQM algorithm at every fixed time interval, they may not be adaptive enough to an abrupt load surge. Further, they can be executed unnecessarily often under light loads due to the time-driven nature. To seamlessly integrate the advantages of both event-driven and control-theoretic time-driven approaches, we present an event-driven feedback control approach based on formal control theory. As our approach is based on a mathematical model, its performance is more analyzable and predictable than ad hoc event-driven approaches are. Also, it is more reactive to dynamic load changes due to its event-driven nature. Our simulation results show that our event-driven controller effectively maintains the queue length around the specified set-point. It achieves shorter E2E (end-to-end) delays and smaller E2E delay fluctuations than several existing AQM approaches, which are ad hoc event-driven and based on time-driven control theory, while achieving almost the same E2E delays and E2E delay fluctuations as the two other advanced control theoretic AQM approaches. Further, our AQM algorithm is invoked much less frequently than the tested baselines.     

改进的AQM在拥塞控制中的应用策略

随着计算机网络的持续快速发展,各种网络需求不断涌现,拥塞控制成为保证网络的稳定性和鲁棒性的重要因素,拥塞控制的发展要求网络本身也要参与其中。传统的端到端机制不能解决所有的拥塞问题,作为主动管理队列算法的REM原算法由于对RTT的不精确估计导致不能准确反应网络中拥塞状态。根据控制论中将链路价格化的方法,对REM算法的进行了改进,提出了新的拥塞控制机制。仿真实验表明,该方法能有效减少包的丢失,提高系统性能。     

控制时延的主动队列管理算法

针对现有的主动队列管理(AQM)算法造成的队列时延无法满足VoIP、音视频等流媒体传输需求的问题,提出一种直接控制队列时延的主动队列管理算法--DCQA。该算法使用PID控制器计算路由器缓存的数据包丢弃概率,用其对即将进入缓存排队的数据包做丢包判断并采取相应动作,以控制队列时延在期望值以下。实验仿真了3种网络环境下DCQA的性能,链路利用率分别是99.93%、99.88%和99.95%。并且,队列时延分别有50.45%、51.59%、52.4%被控制在期望值以下,比CoDel算法分别提高了3.6%、40.53%、50.69%。实验结果表明,DCQA在不同的网络环境中都可以获得较高的链路利用率,而且控制队列时延的能力优于CoDel算法,适用于流媒体的传输。