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.     

一种基于路由器队列法则的增加SRED算法

主动队列管理是网络拥塞控制的主要研究方向.作为一种典型的主动队列管理算法,SRED采用一种负载相关的概率来丢弃报文,使得路由器队列长度处于一个较低的稳定值,从而获得相对稳定的网络延时.但SRED算法在设计初始丢弃概率函数时不能保证函数曲线的平稳过渡,这将导致路由器队列长度不稳定以及不必要地丢弃报文.引入路由器队列法则,对SRED算法的缺陷进行了理论分析,在此基础上设计了一种增强的SRED算法:E-SRED.仿真实验验证了E-SRED算法在保持路由器队列稳定性以及使队列快速收敛方面对SRED算法都有一定的提高.     

基于反馈的区分服务网络拥塞管理方案研究

为了有效解决RED算法拥塞响应滞后以及在聚集类之间公平性不足的问题,提出建立一种基于早期拥塞指示反馈的区分服务网络模型,并在该模型上采用优先级早期随机检测算法。在网络入口节点对分组进行分类、聚集与监测,各队列按优先级设置不同队列长度阈值,当平均队列长度或各队列长度达到相应阈值范围时,立即触发不同程度拥塞指示包向源端反馈。使用改进的NS进行了仿真实验,实验结果表明该算法使得拥塞指示能尽可能快地到达TCP源,有效地降低路由器中的丢包率。提高网络利用率,并且为不同的聚集类提供不同优先级服务,保障了聚集类的公平性。     

Bounds estimation and practical stability of AIMD/RED systems with time delays

The Additive Increase and Multiplicative Decrease (AIMD) congestion control algorithm of TCP deployed in the end systems and the Random Early Detection (RED) queue management scheme deployed in the intermediate systems contribute to Internet stability and integrity. Previous research based on the fluid-flow model analysis indicated that, with feedback delays, the TCP/RED system may not be asymptotically stable when the time delays or the bottleneck link capacity becomes large [3]. However, as long as the system operates near its desired equilibrium, small oscillations around the equilibrium are acceptable, and the network performance (in terms of efficiency, loss rate, and delay) is still satisfactory. In this paper, we study the practical stability of AIMD/RED system with feedback delays and with both homogeneous and heterogeneous flows. We obtain theoretical bounds of the flow window size and the RED queue length, as functions of the number of flows, link capacity, RED queue parameters, and AIMD parameters. Numerical results with Matlab and simulation results with NS-2 are given to validate the correctness and demonstrate the tightness of the derived bounds. The analytical and simulation results provide important insights on which system parameters contribute to higher system oscillations and how to set parameters (such as buffer size and queue management parameters) to ensure system efficiency with bounded delay and loss. Our results can also help to predict and control the system performance for Internet with higher data rate links multiplexed with heterogeneous flows with different parameters.     

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.     

Multi-indicator Active Queue Management Method

A considerable number of applications are running over IP networks. This increased the contention on the network resource, which ultimately results in congestion. Active queue management (AQM) aims to reduce the serious consequences of network congestion in the router buffer and its negative effects on network performance. AQM methods implement different techniques in accordance with congestion indicators, such as queue length and average queue length. The performance of the network is evaluated using delay, loss, and throughput. The gap between congestion indicators and network performance measurements leads to the decline in network performance. In this study, delay and loss predictions are used as congestion indicators in a novel stochastic approach for AQM. The proposed method estimates the congestion in the router buffer and then uses the indicators to calculate the dropping probability, which is responsible for managing the router buffer. The experimental results, based on two sets of experiments, have shown that the proposed method outperformed the existing benchmark algorithms including RED, ERED and BLUE algorithms. For instance, in the first experiment, the proposed method resides in the third-place in terms of delay when compared to the benchmark algorithms. In addition, the proposed method outperformed the benchmark algorithms in terms of packet loss, packet dropping, and packet retransmission. Overall, the proposed method outperformed the benchmark algorithms because it preserves packet loss while maintaining reasonable queuing delay.     

LRED: A Robust and Responsive AQM Algorithm Using Packet Loss Ratio Measurement

Active queue management (AQM) is an effective means to enhance congestion control, and to achieve trade-off between link utilization and delay. The de facto standard, random early detection (RED), and many of its variants employ queue length as a congestion indicator to trigger packet dropping. Despite their simplicity, these approaches often suffer from unstable behaviors in a dynamic network. Adaptive parameter settings, though might solve the problem, remain difficult in such a complex system. Recent proposals based on analytical TCP control and AQM models suggest the use of both queue length and traffic input rate as congestion indicators, which effectively enhances stability. Their response time generally increases however, leading to frequent buffer overflow and emptiness. In this paper, we propose a novel AQM algorithm that achieves fast response time and yet good robustness. The algorithm, called Loss Ratio-based RED (LRED), measures the latest packet loss ratio, and uses it as a complement to queue length for adaptively adjusting the packet drop probability. We develop an analytical model for LRED, which demonstrates that LRED is responsive even if the number of TCP flows and their persisting times vary significantly. It also provides a general guideline for the parameter settings in LRED. The performance of LRED is further examined under various simulated network environments, and compared to existing AQM algorithms. Our simulation results show that, with comparable complexities, LRED achieves shorter response time and higher robustness. More importantly, it trades off the goodput with queue length better than existing algorithms, enabling flexible system configurations     

高带宽无线局域网中PI速率控制算法

针对传统传输控制协议（TCP）在高带宽、无线网络中性能表现不佳的问题, 建立了一个端到端的虚拟路由器模型, 提出了一个端到端的发送端比例积分（PI）速率控制算法。根据RTT的变化, 利用PI控制器计算发送端的发送速率, 使瓶颈节点的队长稳定在一个目标位置, 减少拥塞丢包, 避免无线链路错误丢包引起的对拥塞窗口的错误调整。仿真结果表明, 与传统拥塞控制协议相比, 新机制能较好地控制路由器队长、提高网络负载的稳定性和网络吞吐率。     

一种针对TCP动态队列管理的控制算法

描述了一种新的TCP/IP动态队列管理控制算法,对于传统的随机早期检测法(RED)来说,它的主要目标之一就是稳定路由器队列的长度,然而它实现此目标并不是很成功,主要因为它在平衡队列长度的过程中很强地依赖了动态TCP链接数。而新的动态控制算法则使用了一种简单的控制方法,当路由器缓冲区即将出现拥塞时,它能够根据当前路由器缓冲区负载概率来随机地实施包丢弃。该算法能够很好地稳定路由器缓冲区的队列占用数,同时,在实现过程中并不用评估动态TCP链接数以及分析网络流的状况。所给出的一个实验模型表明,该控制算法是有效可行的。     

基于NS2的主动队列管理仿真研究

主动式队列管理技术是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。该文介绍了目前应用较为广泛的网络仿真器NS-2，对几种主要AQM算法Drop Tail、RED和ARED的性能在基于NS2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、TCP 全局同步问题、连接数对系统稳定性和鲁棒性的影响等；仿真结果表明ARED性能优于Drop Tail和RED算法。     

不确定TCP流模型的离散H∞鲁棒主动队列管理算法

针对TCP/IP网络存在参数时变和不确定性下的拥塞控制问题,提出一种新的基于H∞状态反馈控制的离散鲁棒主动列队管理算法(AQM).该方法针对不确定TCP流模型,将短期突发流所占据的带宽作为系统的外部干扰,同时考虑时滞和参数不确定性因素,基于Lyapunov稳定性理论和线性矩阵不等式技术,设计了离散鲁棒状态反馈控制器以保证路由器队列响应的稳定性和鲁棒性.最后,通过NS-2仿真验证了本文方法的有效性.     

网络拥塞控制模型Hopf分岔的PD控制

网络拥塞会导致信息丢失,时延增加,甚至系统崩溃。由于无线接入网络中的时变衰落和分组错误率,使得TCP协议在网络拥塞控制更加复杂。TCP Westwood是专门为高速无线网络设计的,大大提高了网络带宽的利用率,改善了网络性能。TCP Westwood/AQM拥塞控制的连续流体流模型被引用,源端采用TCP Westwood拥塞控制协议,路由器端采用主动队列管理(AQM)机制中的随机早期检测(RED)算法。为了延迟无线接入网络拥塞控制模型中霍普夫(Hopf)分岔现象的发生,采用比例微分(PD)控制器,通过选择通信延迟作为分岔参数,分析无线网络系统中的Hopf分岔行为,并由理论分析得知当分岔参数超过临界值时系统发生Hopf分岔。利用中心流形和规范型理论,推导得出系统发生Hopf分岔的条件和反映Hopf分岔性质,方向和周期的参数,数值仿真验证理论分析的准确性,表明PD控制器的有效性。     

一种基于Smith预估器的主动队列管理(AQM)拥塞控制算法

有效的拥塞控制机制是保证Internet稳定运行的关键因素之一,网络拥塞控制系统本质上是一个时滞系统,传输时延是网络拥塞控制必须考虑的一个重要因素.本文应用Smith预估控制原理,在进行适当模型拟合处理的基础上,提出了一种基于Smith预估器的主动队列管理(AQM)算法(AQMAlgorithmbasedonsmithpredictor算法,简称Smith-PI),新算法结构简单,易于配置,具有良好的鲁棒性和网络控制性能,同时克服了大时滞给队列稳定性造成的不利影响。通过仿真表明,采用Smith-PI算法,对于限制系统振荡超调量的作用非常明显,同时能使网络具有更快的响应速度及更平稳的队列,而当网络时延增大时,算法能使网络的动态性能依然保持良好,使得缓存队列迅速收敛到稳定值。     

RED算法的数学模型研究

RED算法能够及时预测网络拥塞的到来,并同过标记避免网络拥塞,同时还解决了TCP全局同步的问题.RED算法对参数过于敏感一直是研究的主要问题.建立RED算法的数学模型,从数学角度分析RED算法的原理以及工作过程.对数学模型的静态分析、参数分析研究各个参数在算法中所起的作用以及其影响因子;给出如何设定参数才能使RED算法达到更好的性能.     

基于源端控制规律的主动队列管理算法

将TCP源端的拥塞控制规律引入路由器端的拥塞控制问题,提出一种高性能的主动队列管理算法ERFU,综合考虑路由器输入流的流量速率与内部负载程度,无需设置多样的参数,直接依据TCP源端的拥塞控制规律,更新数据包的丢弃(标记)概率,具有较低的算法需求和优越的算法性能。通过仿真与ERED相比较,证明ERFU在随机流、突发流2种网络状况下均具有更优良的性能。     

一种适于Internet拥塞控制的自校正队列管理算法

1.引言近年来,随着计算机和网络技术的迅猛发展以及多媒体应用的急剧增加,人们对Internet的服务质量提出了更高的要求。虽然目前TCP所采用的基于窗口的端到端拥塞控制机制对Internet的鲁棒性起到了关键性的作用。但传统的去尾(drop-tail)先进先出(FIFO)的队列管理方式,不可避免地会导致过高的传输延迟和延迟抖动。为适应越来越多的实体媒体传输的要求,人们开始研究更为有效的队列管理算法,从而使网络在采用TCP拥塞控制算法的基础上,实现效率最高并尽可能减小路由器中的平均队列长度,即主动队列管理技     

一种基于连接的增强拥塞控制机制

文中针对越来越多的网络应用不采用端拥塞控制机制而导致非公平占用网络带宽问题,介绍了在路由器内部实现基于连接调度的增强拥塞控制方法。路由器使用公平排队调度算法代替传统的先来服务调度算法,可隔离和保护基于漏桶控制的连接。但采用基于窗口反馈拥塞控制机制ＴＣＰ连接会对数据包丢失敏感,路由器使用公平排队调度算法还需要结合相应的缓冲管理方法,才能保证ＴＣＰ连接获取公平的吞吐量。文中还讨论了基于连接的排队数据包     

Dynamics analysis of TCP Veno with RED

This paper studies the dynamics of TCP Veno with the queue management of RED (Random Early Detection). We develop a fluid-flow model to describe the behaviors of TCP Veno in wired/wireless networks. This model is further linearized to study TCP Veno’s stability issue through the linear feedback control theory. The analysis points out how the RED queue oscillates under different network parameters such as link capacity, round-trip time. Simulations are carried to validate our theoretical analysis. Furthermore, based on the analysis results obtained in this paper, we are able to provide guidelines for tuning RED parameters to stabilize the router queue, and improve the co-existence between TCP Veno and TFRC (TCP-friendly Rate Control) flows.     

D-RED：一种改进的路由器拥塞控制算法

本文详细分析了随机早期检测RED拥塞控制机制算法的思想，阐述了RED的不足，提出了一种改进的动态自适应算法D-RED。该算法设置一个平均队列大小的目标值，在实时平均队列大小小于目标值和大于目标值时使最大丢包概率动态地减去和加上一个通过数学方法推导出的同路由器上一次丢包概率有关的值，以达到更好地控制网络拥塞的目的。利用NS2设计多组仿真实验对RED和D-RED性能进行比较，通过对吞吐量、延迟、振荡、丢包率等多项性能指标分析和比较表明，D-RED算法相对于RED算法使网络丢包率降低了15．7％，网络吞吐量提高了9．44％，而且能够在一定程度上保护TCP数据流，使其得到公平的网络资源。