主动队列管理算法的分类器实现

作为端到端拥塞控制的增强机制,主动队列管理(AQM)通过在网络中间节点有目的地丢弃分组来维持较小的队列长度和较高的链路利用率.已有的大多数主动队列管理算法沿用了随机早期探测(RED)算法首创的概率丢弃机制.本质上,判决是否丢弃分组的过程是一个依赖于网络拥塞状态的决策过程,因此,概率决策不应该是唯一的方法.在本文的研究中,我们首先归纳了理想AQM算法所应具备的品质,然后应用模式识别中分类器的设计思想提出了一种新颖简洁的主动队列管理策略实现框架,并基于Fisher线性判别方法为AQM设计了一个两维两类分类器(TCC).仿真试验表明TCC有效、敏捷、鲁棒,扩展性好,同时实现简单,计算开销小,有利于高速路由器的性能优化.     

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。     

动态权重RED网关

随着网络流量的增加,拥塞控制的重要性日益突出,尤其是链路拥塞控制。IETF推荐RED(Random Early Detection)作为下一代Internet路由器的拥塞控制算法。该文在分析了RED的优点和缺点后,在现在RED算法的基础上通过改进RED算法的平均队列长度计算,使用平均队列长度的均值,判断拥塞的发生和结束,动态调整权重,提高RED对拥塞发生和拥塞结束的反应速度,缩短拥塞时间,维持较低的实际队列长度。最后用仿真验证了该方法。     

动态权重调整RED

IETF推荐RED(Random Early Detection)作为下一代Internet路由器的拥塞控制算法.但RED中平均队列长度对实际队列变化反应较慢,导致出现拥塞的时间增加,丢包增多,本文在现有RED算法的基础上通过改进RED算法的平均队列长度计算,使用平均队列长度的均值,判断拥塞的发生和结束,动态调整权重,提高RED对拥塞发生和拥塞结束的反应速度.仿真结果表明算法减少了拥塞时间,能够维持较低的实际队列长度,进而减少了数据包排队时间.     

PRED:一种具有优先级自适应的队列管理新算法

现有的拥塞控制采用以TCP为核心的基于窗口技术的端到端控制,具有丢包、响应速度慢等缺陷.本文提出的基于优先级的队列管理算法(PRED),使路由器更加精确地管理队列,算法的主要参数能够适应网络负载的动态变化,有效地克服了现有拥塞控制的缺陷.实验结果表明,在相同的配置下,采用PRED的网络在降低丢包率、减少队列抖动等性能上均优于端到端拥塞控制.     

一种新的语音流队列管理调度机制

本文提出一种新的语音流队列管理调度机制,结合随机早期探测(RED)和主动丢包调度算法实现因特网语音流的队列管理和调度.采用仿真方法分析了新机制的性能特征,并与RED做了性能对比.当网络拥塞时,该算法可有效改善包转发的性能.语音质量测试表明新机制是可行的和有效的.     

一种基于负载的公平性主动队列管理算法

针对随机早期检测（RED,Random Early Detection）算法存在的公平性问题,提出了一种基于负载的公平性主动队列管理算法（LFED）。该算法通过引入网络负载和队列这两个概念,有效地判断当前网络拥塞程度,同时使用改进的丢包率公式,并且借鉴CHOKe算法的惩罚机制对非响应流进行有效惩罚,以保证不同数据流之间的公平。仿真实验表明,与RED和CHOKe相比,LFED可以得到稳定的瞬时队列长度和减少分组丢弃率,具有较好的公平性和稳定性。     

一种基于模糊逻辑的主动队列管理算法

主动队列管理 (ActiveQueueManagement,AQM)技术作为Internet拥塞控制的一种有效方法 ,对于提高In ternet的服务质量具有十分重要的作用 .本文根据TCP拥塞控制算法基于数据包丢失的窗口变化机制 ,设计了一种基于模糊逻辑的主动队列管理算法 .该算法依据路由器中队列长度的变化情况 ,根据一定的模糊自校正原则来调整数据包的丢弃概率 ,从而使路由器中的队列长度稳定在参考值附近 .仿真结果表明该算法不但十分有效 ,而且对不同的网络状况具有很好的适应能力 .     

一种改进的主动队列调度RED算法

本文在分析RED利用EWMA形式计算平均队列长度的局限性的基础上,提出了一种改进的RED算法。该改进RED算法在计算平均队列长度时考虑了当前队列长度的真实情况,并将两者结合起来进行丢弃决策。仿真结果表明改进RED算法在分组丢弃比例和链路利用率上部优于RED。     

一种参数自适应的主动队列管理算法-自适应BLUE

BLUE算法是一种典型的主动队列管理(Active Queue Management,AQM)算法,研究表明BLUE算法优于RED算法.BLUE算法使用丢包事件和链路空闲事件控制网络拥塞.但由于BLUE算法在参数设置方面存在不足,尤其是当TCP连接数突然剧烈变动时,容易导致队列溢出或空闲的频繁发生.该文引进参数自适应机制,提出了自适应BLUE算法,并借鉴了RED算法的早期拥塞检测机制.NS仿真实验表明该算法能有效保持队列长度的稳定,减少队列溢出或空闲现象的发生,在提高链路利用率的同时降低丢包率.     

一种基于速率和队列长度的主动队列管理机制

本文研究了拥塞产生的原因及其表现形式,提出了一种基于报文到达速率和队列长度的随机早丢弃算法(RQ).根据拥塞的严重程度和变化趋势将拥塞划分为六个级别,每个级别采用合适的丢弃概率,从而将队列控制在理想工作点附近.利用经典控制理论,分析了系统的稳定性,给出了参数配置的原则.最后,用NS网络仿真器对算法性能进行了验证.     

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.     

Random early detection gateways for congestion avoidance

The authors present random early detection (RED) gateways for congestion avoidance in packet-switched networks. The gateway detects incipient congestion by computing the average queue size. The gateway could notify connections of congestion either by dropping packets arriving at the gateway or by setting a bit in packet headers. When the average queue size exceeds a present threshold, the gateway drops or marks each arriving packet with a certain probability, where the exact probability is a function of the average queue size. RED gateways keep the average queue size low while allowing occasional bursts of packets in the queue. During congestion, the probability that the gateway notifies a particular connection to reduce its window is roughly proportional to that connection's share of the bandwidth through the gateway. RED gateways are designed to accompany a transport-layer congestion control protocol such as TCP. The RED gateway has no bias against bursty traffic and avoids the global synchronization of many connections decreasing their window at the same time. Simulations of a TCP/IP network are used to illustrate the performance of RED gateways     

A fuzzy-logic control algorithm for active Queue Management in IP networks

Active Queue Management （AQM） is an active research area in the Internet community. Random Early Detection （RED） is a typical AQM algorithm, but it is known that it is difficult to configure its parameters and its average queue length is closely related to the load level. This paper proposes an effective fuzzy congestion control algorithm based on fuzzy logic which uses the predominance of fuzzy logic to deal with uncertain events. The main advantage of this new congestion control algorithm is that it discards the packet dropping mechanism of RED, and calculates packet loss according to a preconfigured fuzzy logic by using the queue length and the buffer usage ratio. Theoretical analysis and Network Simulator （NS） simulation results show that the proposed algorithm achieves more throughput and more stable queue length than traditional schemes. It really improves a router＇s ability in network congestion control in IP network.     

Designing a binary controller to enhance end-to-end congestion control

Active queue management (AQM) is proposed to enhance end-to-end congestion control through purposefully dropping packets in the intermediate nodes. In this letter, a novel packet dropping mechanism is developed through designing a binary controller applying the robust control theory. The new mechanism can simplify the manipulation on the AQM router so as to be helpful for implementing the high performance router. The numerical simulation results show that the binary controller can satisfy with the technical requirements for AQM     

Ensuring fairness among ECN and non‐ECN TCP over the Internet

Explicit Congestion Notification (ECN) has been proved to provide a fast indication of incipient congestion and thus better the performance of a TCP/IP network. In this work, we carry out investigations on gateway or router performance in providing fairnesss when both FIM ECN‐capable and non‐ECN‐capable connections are employed. We propose a new packet‐dropping scheme called Fair In‐time Dropping (FID) which drops packets from a connection upon detecting an incipient indication of congestion depending on its share of gateway or router buffer occupancy. We also show that a combination of FIM and FID offers the best fairness compared with a combination of FIM along with other dropping schemes. Copyright © 2003 John Wiley & Sons, Ltd.     

RED gateway congestion control using median queue size estimates

This paper focuses on the queue size estimation problem in random early detection (RED) gateways. Queue size estimation plays a fundamental role in the congestion control dynamics of RED, as it determines gateways' awareness of network congestion, which in turn determines the packet dropping/marking decision. Conventional RED gateways use exponentially weighted moving averages (EWMA) to estimate the queue size. These infinite impulse response (IIR) filters require very small EWMA weights in order to effectively avoid nonlinear instabilities in RED and to filter out bursty increases in the queue size. While small EWMA weights enable gateways to accommodate transient congestion, they also lead to gateways' failure to closely track rapid queue size depletion and thus causes link under utilization. We investigate the use of simple nonlinear queue size estimators. In particular, we study the congestion control dynamics of a network where adaptive weighted median filters are used for queue size estimation by the gateways. Analytical results for the expected queue size in the steady state are derived. Under this new queue size estimation framework, design guidelines for the remaining RED parameters are provided. Simulation results show that the proposed algorithm provides greater network power, better prevention of global synchronization, and a fairer treatment to bursty traffic than the RED algorithm does.     

传感器网络拥塞避免与控制的模糊AQM算法

传感器网络节点通信能力有限,当数据到达速率持续超过节点转发能力时网络会发生拥塞;传感器网络是任务型网络,对不同优先级的信息具有不同的服务质量要求.针对传感器网络信息传输的上述特性,提出了一种新的拥塞避免与控制算法FAQM（Fuzzy Active Queue Management）.该算法在综合考虑数据包的随机指数标记概率和优先级权值的基础上,建立了模糊逻辑推理系统,并以数据包丢弃因子作为参量来实现数据流的智能调控.NS2仿真实验结果表明：FAQM算法能减少高优先级数据包的丢弃率和节点间链路的时延,稳定节点队列长度,在有效避免与控制拥塞网络的同时提升网络整体QoS（Quality of Service）性能.