基于参数不敏感设计的网络拥塞控制算法

本文提出了一种新颖的主动队列管理(active queue management,AQM)策略一间隔随机早期检测(interval random earlv detection,IRED).与传统的RED机制不同,IRED的参数设计中,平均队长的门限值一最小阈值和最大阈值从固定不变的单值,变为了一个阈值区间.相对于RED的单值固定阈值的设计,IRED的适应能力和鲁棒性得到增强,在大多数的网络环境下能够保持良好的性能,特别是在网络状态出现波动和突变时,其性能比传统的AQM算法更佳.本文进一步采用了TCP-AQM的动态模型分析了使用IRED控制器的拥塞控制系统的稳定性,分析了系统的稳定裕度,并给出了稳定裕度与控制增益的关系式,从而提出了一种根据期望稳定裕度来设计阈值区间的系统化方法.最后.在NS-2仿真平台上,通过与RED和Gentle-RED种算法比较,证明IRED优越性,特别是在变负载的网络环境下的良好性能.     

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.     

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.     

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.     

图书馆多媒体信息资源网络的自适应传输控制方法

为了增强图书馆多媒体信息的稳健传输和多媒体信息网络的鲁棒性、稳定性,提出了一种新颖的RED策略。最小阈值(minth)和最大阈值(maxth)能够随着缓存队列的平均占用率的变化动态调整,而不再是预设的固定参数。改进后,ATRED对路由器队列的控制力度能够根据网络环境的变化自适应调整,使得队长方差减小,队列振荡变小,网络更加稳定,能够在复杂多变的网络环境下提供更加可靠的服务。     

适用于异质网络的RED算法的改进与分析

设计、分析和评价主动队列管理(AQM)算法成为近来网络拥塞问题研究的一个热点.随机提前探测(RED)算法作为AQM算法的典型代表,得到了较为广泛的应用.为了提高它的稳定性和公平性相继又开发出了ARED(adaptive RED),GRED(gentle RED),FRED(flow RED)和wRED(weighted RED)等多种改进算法.在分析了RED算法及3种变种算法的基础上,比较了它们的优缺点,给出了适用于不同性质网络连接点处的WRED改进算法,用仿真试验证明了WRED改进算法在处理异质网络拥塞问题方面具有优势.     

基于智能预测控制的网络拥塞主动队列管理算法研究

路由队列管理是保证网络性能、避免网络拥塞的重要手段,目前采用的主要队列管理方法为被动式队列管理,同时主动式队列管理已经成为近来的主要研究热点. 随机早侦测(RED)作为最早提出的主动队列管理方法,更获得了普遍的关注. 使用严格的数学模型来描述由端系统和网关组成的系统,并进行队列管理性能分析. 提出一种采用快速广义预测控制的RED控制器( FGPC2RED控制器) ,进行网络拥塞控制的研究. 介绍了系统的结构及系统的辨识, 并通过仿真证明了FGPC算法在路由队列管理中应用的可行性,可以有效控制队列长度,避免路由拥塞及减小往返延迟.     

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.     

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     

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．     

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.     

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.     

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。     

随机早期检测主动队列管理算法的改进研究

主动队列管理（Active Queue Management）算法是近几年网络研究的重点。为了改进和完善现有的AQM算法和设计更好的新算法,需要对主动队列管理机制的实现方法和性能特性进行深入研究,详细讨论了随机早期检测（Random Early Detection）主动队列管理机制的关键技术问题,研究了近年来对RED算法的主要改进算法,总结了这几种算法的优缺点及其有待改进之处,并应用网络仿真器（Network Simulator）对实际网络模型进行了仿真实验,检验了改进算法对网络性能的影响。     

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.     

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].