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.     

On the use of a full information feedback to stabilize RED

RED and most of its family algorithms use only the average queue length as a congestion meter. Since the average queue length considers only long-term behavior of the queue, these algorithms fail to see instantaneous changes of the queue length and hence their reaction to the congestion is not fast enough. In other words the feedback generated by using only the average queue length does not reflect the network congestion precisely and hence leads to a poor performance and stability. This paper solves this problem by designing a RED-based active queue management (AQM) algorithm, called FUF-RED that provides a Full Information Feedback. This algorithm not only considers the average queue length but also it takes into account growth rate of the instantaneous queue length to calculate its congestion feedback. The proposed algorithm is supported by a theoretical stability analysis which gives those feedback gains that guarantees the network stability. Extensive packet level simulations, done by using ns-2 simulator, show that the proposed algorithm outperforms existing AQM algorithms in terms of stability, average queue length, number of dropped packets and bottleneck utilization.     

Design and analysis of a self-tuning feedback controller for the Internet

Active queue management (AQM) is an effective method used in Internet routers for congestion avoidance, and to achieve a tradeoff 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. This paper proposes a novel packet dropping scheme, called self-tuning proportional and integral RED (SPI-RED), as an extension of RED. SPI-RED is based on a self-tuning proportional and Integral feedback controller, which considers not only the average queue length at the current time point, but also the past queue lengths during a round-trip time to smooth the impact caused by short-lived traffic dynamics. Furthermore, we give theoretical analysis of the system stability and give guidelines for selection of feedback gains for the TCP/RED system to stabilize the average queue length at a desirable level. The proposed method can also be applied to the other variants of RED. Extensive simulations have been conducted with ns2. The simulation results have demonstrated that the proposed SPI-RED algorithm outperforms the existing AQM schemes in terms of drop probability and stability.     

Performance evaluation for DRED discrete-time queueing network analytical model

Due to the rapid development in computer networks, congestion becomes a critical issue. Congestion usually occurs when the connection demands on network resources, i.e. buffer spaces, exceed the available ones. We propose in this paper a new discrete-time queueing network analytical model based on dynamic random early drop (DRED) algorithm to control the congestion in early stages. We apply our analytical model on two-queue nodes queueing network. Furthermore, we compare between the proposed analytical model and three known active queue management (AQM) algorithms, including DRED, random early detection (RED) and adaptive RED, in order to figure out which of them offers better quality of service (QoS). We also experimentally compare the queue nodes of the proposed analytical model and the three AQM methods in terms of different performance measures, including, average queue length, average queueing delay, throughput, packet loss probability, etc., aiming to determine the queue node that offers better performance.     

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.     

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.     

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。     

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。     

一种基于负载和队列的模糊主动队列管理算法

针对目前已有的模糊主动队列管理算法(AQM)大多只考虑队列长度及其变化率作为模糊输入,很少同时考虑包到达速率的影响,结合队列长度和包到达速率,提出一种更为有效的模糊主动队列管理算法(FQL-AQM)。FQL-AQM以瞬时队列长度和网络平均负载因子作为模糊输入来调整包丢弃概率,并采用参数自校正技术,将队列长度维持在期望的队列水平上、包到达速率维持在队列服务速率附近,使算法对网络状态的变化具有很好的适应能力,从而提高网络的鲁棒性。仿真结果表明,FQL-AQM算法具有比FQ-AQM算法更快的响应速度、更高的链路利用率和更好的队列稳定性,从而减少了分组延时抖动和分组丢弃率。     

一种链路负载自适应的主动队列管理算法

随机早检测(random early detection,简称RED)是IETF推荐部署的主动队列管理(active queue management,简称AQM)算法.RED存在参数难以配置、无法得到与流量无关的平均队长等问题.ARED(adaptive RED)是RED的自适应版本,它根据平均队长动态调节最大标记概率参数,从而得到稳定的平均队长.但ARED没有克服瞬时队列长度振荡问题,且在动态流量环境下性能明显降低.分析了ARED性能问题的原因,并提出了一种链路负载自适应的主动队列管理算法LARED(load adaptiveRED).LARED具有两个特点:自适应链路负载、快速响应队长变化.分析和仿真实验表明,与ARED等其他AQM算法相比,LARED在保持高链路利用率和低时延的同时可以得到稳定的瞬时队长,并且具有良好的响应性和鲁棒性.     

An interval-based congestion control algorithm under varying network conditions

A new IRED (interval random early detection) congestion control algorithm is proposed for network congestion avoidance and resource management. Different to the traditional AQM (active queue management) algorithms, the control parameters of IRED are not configured statically, and is setting as a parameter interval according to the changes of network environment. By the interval parameter design, the IRED alleviates the tuning difficulty of RED (random early detection) and shows a robust performance than RED under varying network conditions. It is proved that the stability and stability margin of the IRED control system can be guaranteed. A systematic design method for the configuration of parameter interval is proposed. Simulation studies show the proposed IRED algorithm achieves a robust control performance in varying network environment, which is superior to the RED and Gentle-RED algorithm.     

基于速率和队长的大时滞网络AQM算法

针对网络拥塞控制系统在大时滞网络中产生的不利影响,提出一种基于速率和队长的大时滞网络AQM算法。该算法采用缓冲区队列长度和包到达速率作为网络拥塞的判别依据,在结合Smith预估的模糊PID控制方法中加入速率控制项。仿真表明该算法在大时滞和网络动态变化的环境中拥塞响应较快、收敛时间短,并能较好地将队列长度稳定到期望值附近,提高缓冲区的利用率。     

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.     

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。     

主动队列管理中P I 字节模式和包模式

主动队列管理(AQM)是近年来TCP端到端拥塞控制的一个研究热点，其中PI拥塞控制机制是建立在RED拥塞控制基础上的一种控制机制．PI机制基于两种方法控制网络拥塞现象：跟踪实时队列长度及拥塞情况下以一定概率丢弃到达队列的数据包．以上方法的计算可以基于包数目或字节数，而方法选择的不同对网络会产生不同的影响．仿真量化性地测定使用不同队列计算和标注方法情况下对通信性能产生的影响．同时，PI控制器与RED控制器在相同模式和参数设置下进行比较，可显示出PI控制具有一定的优越性．     

主动队列管理算法的研究

队列管理机制是实现网络拥塞控制的一项重要技术,以往采用的大多都是被动的队列管理机制,而主动队列的管理是根据网络结点的队列长度的变化进行提前丢包,对网络的拥塞进行预先通知,从而减少和避免网络拥塞,提高服务质量.为了对主动队列管理机制进行研究,对IEFT推荐的RED算法作介绍,与传统的被动管理机制Droptail作比较,并且通过网络仿真器NS2对算法进行模拟与分析,指出算法的优缺点,为进一步研究AQM算法提供依据.     

大时滞网络中的拥塞控制算法

主动队列管理(AQM)通过网络中间节点有目的的分组丢弃实现了较低的排队延时和较高的有效吞吐量,是近年来TCP端到端拥塞控制的一个研究热点.已有的大多数AQM算法在设计过程中都没有充分考虑到大时滞对算法性能的影响.首先通过仿真试验证实了已有的几种典型算法控制的队列在大时滞网络中无一例外地出现了剧烈的振荡,导致瓶颈链路利用率下降和延时抖动加剧.为此,在进行了适当模型拟合处理的基础上,应用控制理论中的内模补偿原理设计了鲁棒的延时补偿主动队列管理(delay compensation-active queue management,简称DC-AQM)算法,克服了大时滞给队列稳定性造成的不利影响.仿真实验结果表明,新算法在大时滞小期望队列长度的网络配置中表现出的综合性能明显优于已有的算法,链路利用率是其他算法的3～4倍.     

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.     

IP网络中积极队列管理综述

积极队列管理是IP网络拥塞控制的主要手段之一．本文从控制理论的角度描述带有 积极队列管理的端到端的拥塞控制系统结构，介绍了网络系统受控对象的一种传递函数模型 ，综述了基于该模型的RED参数整定，以及P、PI、自适应控制等积极队列管理算法的设计和 分析，指出受控网络模型精度、控制器的鲁棒性等进一步的研究方向．