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．     

NS2中新协议的实现

深入分析了网络仿真器NS2的组成和结构,以及NS2中队列管理算法的实现机制,在此基础上,通过一个新的主动队列管理算法的设计与实现阐述了在NS2中实现新协议、新算法的方法。新算法主要通过更为准确的拥塞检测和更为合理的分组丢弃概率计算来提高主动队列管理算法的稳定性,最后通过仿真实验对新算法的性能进行了测试,实验结果表明新算法的性能要优于RED算法。     

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。     

一种基于层次速率编码的公平的主动队列管理算法

针对核心无状态的公平队列管理算法的不足,提出一种基于速率编码的新算法。这种方法在压缩的速率共享的空间中进行层次速率编码,更精确地保证最大最小的速率公平性。对非响应流实施有效的惩罚,提高算法的公平性。通过合理的层次分组丢弃对队列的到达速率进行控制,并采用索引的方式管理队列从而具有更好的缓冲区利用率。对算法的性能作实验分析,结果表明改进算法拥有良好的网络带宽利用率和公平性,具有较好的性能。     

主动队列管理中RQC 控制器的设计

基于网络中输入输出速率和队列长度均可帮助决定更精确丢弃概率的思想，提出了根据输入输出速率和队列长度决定包的丢弃标注概率的AQM算法，即RQC算法．通过仿真将该算法与RED和PI算法进行比较，说明了RQC控制算法的优点．     

NARED:一种非线性自适应RED拥塞控制机制

分析了RED及其改进算法的原理和局限性，提出了一种非线性自适应RED拥塞控制机制．该算法利用一个高阶分组丢弃函数，在下限阈值附近以较低的概率标记丢弃分组，在上限阚值附近迅速提高分组的标记丢弃概率；其参数Pmax可依据平均队列和瞬时队列长度自适应调整，避免了静态参数设置的约束，并实现了从部分到全部标记丢弃分组的平滑化．实验仿真结果表明该算法有效提高了缓存区利用率，避免了缓存区的溢出，提高了网络的稳定性与可靠性．     

DiffServ模型中的多级主动缓冲管理算法

根据DiffServ模型实现的需要，在分析现有缓冲管理算法的基础上，提出了QPRED和VPRED多级主动缓冲管理算法，这两种算法在分组分类的粒度上提供了分级的缓冲管理能力，并将每一类分组的缓冲状态（缓冲字节数或缓冲平均队列长度）引入到了分组丢弃概率的计算中，同时结合优先级因子实现了类和类之间在优先级意义上的公平性，与现有的缓冲管理算法相比，QPRED和VPRED多级主动缓冲管理算法更适合于DiffServ模型的要求。     

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。     

一种精确度加强的主动队列管理算法PEBLUE

主动队列管理是IP拥塞控制的一种重要机制，BLUE算法作为一种典型的主动队列管理算法，使用丢包和连接空闲；件来控制拥塞，但是其性能还不稳定．本文对BI。UE算法进行了改进，提出了一种精确度加强的主动队列管理算法—PE-BLUE（Precision Enhanced BLUE），它能自适应地调整其参数．仿真表明PEBLUE能够进一步提高对队列的控制精确度，改善BLUE算法的性能．     

基于混合流拥塞控制的Ad Hoc网络视频传输

基于TCP反馈的主动队列管理算法会无差别地丢弃UDP分组,导致视频质量下降.根据TCP/UDP发送特性和混合流排队机制,推导拥塞窗口、丢弃概率及混合流队列长度的微分方程,通过线性化获得Ad Hoc网络混合流AQM(active queue management)控制模型,提出了一种减少UDP丢弃率的PI-V主动队列管理算法.当视频画质下降时,算法依据视频帧权重与分组长度,动态地调整UDP视频流的丢弃概率.NS(network simulator)仿真表明,PI-V算法优于PI与去尾算法,提高了视频传输质量0.82 d B~2.22 d B的峰值信噪比(PSNR).     

基于平均变化率和空闲长度的丢包概率模型

针对RED队列丢包概率模型在计算丢包概率时精确性不足且未考虑网络流量的自相似性问题,提出了基于数据包入队速率平均变化率和队列空闲长度的队列丢包概率模型（DRED）,给出了相应的实现算法。DRED将网络流量状态引入到丢包概率的计算过程中,丢包概率随着网络流量状态的变化而变化,克服了RED队列丢包概率模型在平均队列长度大于队列最大阈值小于队列最大长度时直接将到达的数据包全部丢弃的弊端。实验结果表明,与RED相比,DRED丢包概率的计算更加精确,丢包率有所降低,吞吐量相对提高,端到端时延虽稍有增大,但时延抖动较小,网络的整体性能有一定提高。     

一种基于速率的公平队列管理算法

针对主动队列管理算法普遍存在的公平性问题,提出基于速率的公平队列管理算法RFED。该算法根据分组的到达速率调节丢包率,将队列的到达速率控制在链路的服务速率下,根据非响应流UDP数据包空间分布特点,对非响应流实施有效的惩罚,以保证不同数据流之间的公平。NS仿真实验表明,该算法在公平性、稳定性等方面效果良好,无需进行复杂的参数配置,容易在现有网络中实施。     

一种支持优先级标记处理的主动队列管理机制

随着Internet流量的日益增加,依赖平均队列长度管理拥塞控制的RED(random early detection)队列管理算法有其内在的缺点,即使结合IETF(Internet engineering task force)明确的拥塞通知ECN(explicit congestion notification)也不能有效地阻止包丢失.在分析比较RED算法和BLUE算法的基础上,提出了一种加强的主动队列管理机制--EBLUE(enhanced BLUE),然后结合EBLUE研究了TCP的拥塞控制机制,     

CARED: Cautious Adaptive RED gateways for TCP/IP networks

Random Early Detection (RED) is a widely deployed active queue management algorithm that improves the overall performance of the network in terms of throughput and delay. The effectiveness of RED algorithm, however, highly depends on appropriate setting of its parameters. Moreover, the performance of RED is quite sensitive to abrupt changes in the traffic load. In this paper, we propose a Cautious Adaptive Random Early Detection (CARED) algorithm that dynamically varies maximum drop probability based on the level of traffic load to improve the overall performance of the network. Based on extensive simulations conducted using Network Simulator-2 (ns-2), we show that CARED algorithm reduces the packet drop rate and achieves high throughput as compared to RED, Adaptive RED and Refined Adaptive RED. Unlike other RED based algorithms, CARED algorithm does not introduce new parameters to achieve performance gain and hence can be deployed without any additional complexity.     

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.     

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.     

一种选择性丢包机制的分析与设计

随机早期捡测算法(RED)在产生丢包时简单地丢弃到达的数据包，由于Web流占据了网络上75％左右的带宽，而Web流的特点是数据包比较少，这就使得早期丢包的效果难以体现。本文提出一种选择性丢包机制，引进一个类似公平队列的虚队列，检测发遥速率过大的流，筛选出丢包的候选链接，拥塞时丢弃候选链接在队列申的第一个连接的数据包。模拟实验结果表明，与队头丢包相比，采用选择性丢包的RED算法可进一步降低网关的丢包率，提高吞吐率，缩短Http的响应时间，提高队列的稳定性。     

A framework to determine bounds of maximum loss rate parameter of RED queue for next generation routers

Random early detection (RED) is expected to eliminate global synchronization by random active packet drop. Its packet drop probability is decided by the maximum packet drop probability in its drop function, buffer thresholds, and average queue length. It has been observed that for a large number of connections, a small value of the maximum packet drop probability may not eliminate global synchronization. Furthermore, since RED uses four parameters to regulate its performance, it is necessary to relate its maximum drop probability with those parameters. The objective of this paper is to develop a framework for the bounds of the maximum drop probability of RED, based on TCP channel model and traffic characteristics. The value of the maximum drop probability obtained by our model will make RED queue achieve its targeted goals.     

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S排队的被动队列管理算法

为了解决网络拥塞问题,基于“弃头”方式建立了一种新的被动队列管理算法（DFSQ）。该算法首先利用S排队推导网络队长的数学表达式,并提出丢包概率和丢包策略。同时,通过仿真实验深入研究了影响网络队长的关键因素,并将DFSQ与随机早期检测算法(RED)、“弃尾”算法进行对比分析,结果表明DFSQ算法性能更优。