SABlue:一种带加速因子的自适应AQM算法

该文在分析SBlue算法的基础上,提出了一种带加速因子的自适应AQM算法SABlue(Self-tune Accelerate Blue)。算法将瞬时队长作为早期拥塞检测参量,根据队列负载因子控制丢包步长,实现丢包概率幅度的自适应调整,最终将路由队列长度稳定在目标区域内。为了提高网络突变跨度较大情况时算法的响应速度,在队列警戒区域内引入了加速因子。实验表明,SABlue面对突变流和不同RTT的网络场景,队列收敛时间短,丢包率小,且具有较好的鲁棒性,算法综合性能优于其他AQM算法。     

一种时滞网络自适应主动队列管理算法研究

主动队列管理(AQM)算法的自适应能力和克服滞后性不良影响的能力是该文研究的重点。在分析AQM采用传统PID存在的问题的基础上,提出了一种时滞网络的自适应主动队列管理(FAGPID)算法。由模糊控制器实现PID参数对动态网络环境的在线自适应调整;成功引入灰预测算法实现反馈数据的超前预测,补偿滞后。仿真对比AQM环境中FAGPID,传统PID以及基于模糊免疫PID(FIGPID)的算法,可知FAGPID相对于FIGPID复杂度低,但FAGPID与FIGPID性能相当,均能克服滞后的影响,能快速稳定地适应动态网络环境,收敛于期望队列长度,具有较小的丢包率,优于传统PID算法。     

基于模糊神经网络的拥塞控制算法研究

本文介绍一种基于模糊神经网络的主动队列管理(AQM)算法,实现网络拥塞控制。利用神经网络来实现模糊推理,可自适应修正隶属函数的参数和加权系数,优化模糊逻辑控制器,从而达到某种性能指标的最优化。仿真结果表明,采用模糊神经网络进行流量速率预测的拥塞控制策略能够使缓冲器队列长度快速收敛到目标值,并且维持小的队列震荡。结果也表明该方法与传统的PD控制器相比具有更好的性能和鲁棒性。     

PAQM: an adaptive and proactive queue management for end‐to‐end TCP congestion control

Two functions, the congestion indicator (i.e. how to detect congestion) and the congestion control function (i.e. how to avoid and control congestion), are used at a router to support end‐to‐end congestion control in the Internet. Random early detection (RED) (IEEE/ACM Trans. Networking 1993; 1 (4):397–413) enhanced the two functions by introducing queue length averaging and probabilistic early packet dropping. In particular, RED uses an exponentially weighted moving average (EWMA) queue length not only to detect incipient congestion but also to smooth the bursty incoming traffic and its resulting transient congestion. Following RED, many active queue management (AQM)‐based extensions have been proposed. However, many AQM proposals have shown severe problems with detection and control of the incipient congestion adaptively to the dynamically changing network situations. In this paper, we introduce and analyse a feedback control model of TCP/AQM dynamics. Then, we propose the Pro‐active Queue Management (PAQM) mechanism, which is able to provide proactive congestion avoidance and control using an adaptive congestion indicator and a control function under a wide range of traffic environments. The PAQM stabilizes the queue length around the desired level while giving smooth and low packet loss rates and high network resource utilization. Copyright © 2004 John Wiley & Sons, Ltd.     

TCP-AQM拥塞控制机制的稳定性-时间域方法

文章讨论了TCP—AQM拥塞控制机制的稳定性问题。基于一类为人熟知的TCP非线性模型，我们利用现代控制理论解决了若干网络拥塞控制中的控制器的参数设计问题。文章首先讨论了一类典型的时滞系统，并从此出发．给出了设计在存在网络传输延迟、负载水平变化的情况下的多种控制器的参数设计准则。我们还展望了网络拥塞问题的随机时滞模型。     

SBlue:一种增强Blue稳定性的主动式队列管理算法

主动式队列管理(AQM)是 IETF 为解决 TCP 端到端拥塞控制机制存在的问题而提出的一种队列管理技术。Blue 是一种常用的 AQM 算法,它使用丢包事件和链路空闲事件来管理拥塞。相比较于 RED 算法,Blue 有很多优点,但由于缺乏早期拥塞检测机制,因此不能维持队列长度的稳定,特别是当 TCP 连接很多或 TCP 连接数发生突变时容易导致队列溢出或空闲。本文为此提出了一种增强 Blue 稳定性的主动式队列管理算法 SBlue。仿真实验表明,SBlue 能有效保持队列长度的稳定,大大减少队列溢出或空闲现象的发生。     

基于平均队列长度和滞留时间的RED算法

在无线通信网络环境下，提出了一种改进的基于平均队列长度和滞留时间的RED算法。这种算法根据平均队列长度和滞留时间计算数据包的丢弃概率，比传统的单纯基于平均队列长度的RED算法相比较，能更有效地实现无线网络中的拥塞控制。     

Design of Active Queue Management System for Scalable TCP in High Speed Networks

The Scalable Transmission Control Protocol (TCP), based on a multiplicative increase, multiplicative decrease congestion avoidance algorithm, has been proposed recently to overcome the inability of Standard TCP to utilize the full bandwidth in high speed networks. This paper employs a novel approach to derive a transfer-function model of Scalable TCP that is then employed in a control-theoretic design of random early detection (RED)-based active queue management (AQM) for such a network. Robust stability of the proposed scheme is established under prescribed conditions, and the design is validated by discrete-event simulations using the ns2 tool. This work was supported by a Gledden Visiting Senior Fellowship for the first author.     

TCP网络的自适应非奇异终端滑模控制

针对TCP网络的拥塞控制问题,采用非奇异终端滑模控制理论提出了一种新的主动队列管理算法。采用非奇异终端滑模面以克服传统终端滑模控制的奇异问题,同时确保系统能在有限时间内收敛至平衡点。考虑到UDP流干扰的情况,用Lyapunov稳定性方法给出了一个自适应律来消除UDP流干扰对系统的影响。仿真结果表明,该算法可以使队列长度快速收敛到设定值,同时维持较小的队列振荡,优于传统的滑模控制。     

An effective network congestion control method for multilayer network

The congestion control problem in a single node network has been solved by the nonlinear feedback control method,which has been proven to be effective and robust for different router’s queue size.However,these control models are based on the single layer network architecture,and the senders and receivers are directly connected by one pair of routers.With the network architecture being more and more complex,it is a serious problem how to cooperate many routers working in the multilayer network simultaneously.In this paper,an effective Active Queue Management（AQM）scheme to guarantee the stability by the nonlinear control of imposing some restrictions on AQM parameter in multilayer network is proposed.The nonlinear control can rely on some heuristics and network traffic controllers that appear to be highly correlated with the multilayer network status.The proposed method is based on the improved classical Random Early Detection（RED）differential equation and a theorem for network congestion control.The theorem proposed in the paper proved that the stability of the fluid model can effectively ensure the convergence of the average rate to its equilibrium point through many routers in multilayer network.Moreover,when the network capacity is larger,the proposed scheme can still approach to the fullest extensibility of utilization and ensure the stability of the fluid model.The paper reveals the reasons of congestion control in multilayer network,provides a theorem for avoiding network congestion,and gives simulations to verify the results.