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.     

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.     

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。     

RED队列稳态误差分析

主动队列管理在保证较高吞吐量的同时，通过在交换节点上主动丢弃数据包来控制队列长度，从而实现对端到端的延时和抖动的控制．RED算法是目前应用最为广泛的主动队列管理(AQM)算法．RED算法以平均队列长度作为衡量网络拥塞的指标，其参数设置对算法性能有较大影响．利用现代控制工程理论，将RED算法看做一种单位反馈控制系统，并将期望队列长度作为系统输入，将瞬时队列长度作为输出，对该系统的稳态误差进行了分析．实验结果表明在稳定状态下，RED队列的波动受分组丢弃概率函数的斜率影响．在稳定条件边界附近，系统的稳态误差急剧增加．     

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.     

Stochastic controller as an active queue management based on B-spline kernel observer via particle swarm optimization

Given the fact that the current Internet is getting more difficult in handling the traffic congestion control, the proposed method is compatible with the stochastic nature of network dynamics. Most conventional active queue management is based on the first stochastic moment. In stochastic theory, the first moment is not efficient for non-Gaussian systems that are the same as the network queue size. We propose a new stochastic active queue management technique, based on stochastic control and B-spline window observer, called intelligent probability density function AQM (IPDF-AQM). The IPDF-AQM is based on a PDF control and particle swarm optimization, which not only considers the average queue length at the current time slot, but also takes into consideration the PDF of queue lengths within a round-trip time. We provide a guideline for the selection of the probability of dropping as control input for TCP/AQM system to make the PDF of queue length converge at a certain PDF target based on B-spline approximation and improve the network performance. Simulation results show that the proposed stochastic AQM scheme does improve the end-to-end performance.     

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。     

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.     

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     

基于ARED的主动队列管理改进算法

随机早期检测（Random Early Detection,RED）是IETF推荐部署的主动队列管理（Active Queue Management,AQM）算法。 RED存在参数难以配置、无法适应动态网络环境的缺点。 ARED（ Adaptive RED）是RED的自适应版本,通过平均队列长度来动态调整最大丢弃概率,从而达到稳定平均队列长度的目的,但是存在瞬时队列长度振荡的问题。文中研究了拥塞控制中的主动队列管理,对ARED算法进行了改进,优化丢弃概率计算函数,提出TTS-ARED算法,实现在动态网络环境下队列长度的稳定以及丢包率降低。 NS2的仿真结果表明,TTS-ARED算法显著地降低了丢包率,队列长度稳定性比ARED算法更优越。     

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.     

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.     

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.     

Adaptive mechanism-based congestion control for networked systems

In order to assure the communication quality in network systems with heavy traffic and limited bandwidth, a new ATRED (adaptive thresholds random early detection) congestion control algorithm is proposed for the congestion avoidance and resource management of network systems. Different to the traditional AQM (active queue management) algorithms, the control parameters of ATRED are not configured statically, but dynamically adjusted by the adaptive mechanism. By integrating with the adaptive strategy, ATRED alleviates the tuning difficulty of RED (random early detection) and shows a better control on the queue management, and achieve a more robust performance than RED under varying network conditions. Furthermore, a dynamic transmission control protocol–AQM control system using ATRED controller is introduced for the systematic analysis. It is proved that the stability of the network system can be guaranteed when the adaptive mechanism is finely designed. Simulation studies show the proposed ATRED algorithm achieves a good performance in varying network environments, which is superior to the RED and Gentle-RED algorithm, and providing more reliable service under varying network conditions.     

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.     

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 .     

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。     

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.     

具有通信时延的AQM控制算法的稳定性

具有通信时延的AQM控制算法是一个复杂的动态非线性反馈系统．为了调查通信时延对Internet服务质量的影响,借助广义Nyquist判据研究了具有通信时延的AQM策略的稳定性．通过对网络系统的传递函数的分析,得到了各通信回路时延相同和时延不同条件下网络系统在平衡点的稳定性判据．这些结论表明,影响Internet性能的关键因素之一的通信时延在Internet通信过程中起着重要的作用．最后仿真验证了该判据的有效性．