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.     

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。     

一种改进的RED主动队列管理算法

主动队列管理（Active Queue Management, AQM）算法是网络拥塞控制中非常重要的研究领域之一。为了使RED算法丢包概率的计算更加平滑,本文在RED-r的基础上对其丢包概率的计算进行了改进,提出了一个名为IMRED-r的新算法,采用分段二次圆函数计算丢包概率,实现了动态网络环境中队列长度的稳定,并且减少了参数的设置。基于NS2的仿真结果表明,IMRED-r算法在复杂的网络环境里具有更好的鲁棒性和稳定性,比RED、RED-r主动队列管理算法优越。     

一种改进的RED主动队列管理算法

主动队列管理(ActiveQueueManagement,AQM)算法是网络拥塞控制中非常重要的研究领域之一。为了使RED算法丢包概率的计算更加平滑,文中在RED-r的基础上对其丢包概率的计算进行了改进,提出了一个名为IMRED-r的新算法,采用分段二次圆函数计算丢包概率,实现了动态网络环境中队列长度的稳定,并且减少了参数的设置。基于NS2的仿真结果表明,IMRED-r算法在复杂的网络环境里具有更好的鲁棒性和稳定性,比RED、RED-r主动队列管理算法优越。     

鲁棒的主动队列管理新算法

作为对终端系统上拥塞控制的一种补充，中间节点上的主动队列管理（AQM）策略在保证较高吞吐量的基础上有效地控制队列长度，从而实现了控制端到端的时延，保证QoS的目的，随机早期检测（RED）及其派生算法虽可以实现AQM的技术目标，但算法的设计要么是依赖于直觉的，要么将网络视为不变定常系统，使得最终形成的算法在稳定性和鲁棒性方面存在不少问题，在该文的研究中，作者将TCP的流量控制过程等效为二阶线性时变系统，采用滑膜变结构这种不敏感控制对象参数和负载扰动的控制器设计方法，设计出一种新的AQM算法，仿真试验表明它的稳态和瞬态性能都优于与它具有相同实现复杂度的RED和PI算法，并且在负载扰动和参数变化时具有很强的鲁棒性。     

基于延时补偿结构的大时滞网络拥塞控制

研究和分析了几种典型的主动队列管理AQM(Active Queue Management)算法在大时滞网络下的稳定性、性能及响应速度,发现如RED、PI等AQM算法在大时滞网络环境下队列出现剧烈的振荡和空队列增多,这些现象直接导致链路利用率降低和丢包率增大.针对上述的大时滞网络,将具有正反馈的延时补偿结构用于TCP/AQM拥塞窗口动态模型,实现对延时的补偿,仿真表明采用该控制结构提高了网络的性能.     

基于Dahlin算法的主动队列管理控制机制研究

主动队列管理 (AQM)是网络中间节点通过一定的分组丢弃策略来达到较低排队时延和较高吞吐量的一种机制。已有多种AQM算法被提出，但绝大多数没有考虑较大的RTT(往返时间)对算法性能的影响。该文针对大RTT的网络环境，实现了一种基于控制理论中Dahlin算法的AQM机制并分析了系统的稳定性和参数选择的准则。仿真实验结果表明，该算法在RTT较大的情况下稳定性、响应速度和鲁棒性都优于随机早期检测(RED)算法和比例－积分(PI)算法。     

一种基于可变结构的主动队列管理算法

主动队列管理算法(AQM)是近年来网络拥塞控制的研究热点之一,已经提出了许多的主动队列管理算法,例如:RED,ARED,SRED,PI,REM等.文中设计一种基于控制理论的可变结构的主动队列管理.通过分析控制机制对于非线性的TCP/AQM模式的鲁棒性和性能,展示了在不确定的RTT(round-trip time)和活跃的TCP连接个数的情况下,有很好的性能和鲁棒性,这正是主动队列管理最重要的理念.运用网络仿真软件NS对设计进行仿真验证,从不同的角度对其性能与现有队列管理算法进行比较.仿真结果显示,从稳定性和鲁棒性等角度,可变结构控制算法显著胜过现有的AQM算法     

基于数字化图书馆综合业务流的网络控制方法

针对数字图书馆网络的服务质量控制问题,提出了RED阈值动态调整的自适应机制,缓解了RED的参数的敏感性,增强了RED自适应性、鲁棒性,实现了一种基于RED的AQM新策略――Adaptive Threshold RED（ATRED）。为了更好的分析ATRED的控制性能,在不同的网络环境下ATRED与RED和GENTLE RED的控制性能进行了比较,使用NS-2进行仿真,仿真结果表明,自适应性增强的ATRED算法对队列的控制更为有效,队列的振荡相对较小,能为用户提供更为稳定可靠的服务质量。     

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.     

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.     

Per-stream loss behavior of ∑MAP/M/1/K queuing system with a random early detection mechanism

In this paper, the matrix-analytic approach is applied to explore the per-stream loss behavior of the multimedia traffic under RED scheme. We constructed a ∑MAP/M/1/K queuing model for the RED mechanism with multimedia traffic which follows a continuous-time Markovian arrival process (MAP). In addition to evaluating the long-term per-stream packet drop probabilities, we examine the bursty nature of per-stream packet drops by means of conditional statistics with respect to dropped periods and the probability that the queuing system stays in the dropped period. The dropped period corresponds to having more than a certain number of packets in router buffer; non-dropped period corresponds to the opposite. These performance measures describe the quality of service provided by the router to particular multimedia traffic streams in the presence of background multimedia traffic.     

Effective RED: An algorithm to improve RED's performance by reducing packet loss rate

Random early detection (RED) is an effective congestion control mechanism acting on the intermediate gateways. We describe a new active queue management scheme, Effective RED (ERED) that aims to reduce packet loss rates in a simple and scalable manner. We made a few change to packet drop function of existing RED scheme. The rest of the original RED remains unchanged. We achieve this by making several refinements and by controlling packet dropping function both with average queue size and instantaneous queue size. Simulations demonstrate that ERED achieves a highest throughput and lowest packet drops than RED, Blue, REM, FRED, LDC and SRED. Since ERED is fully compatible with RED, we can easily upgrade/replace the existing RED implementations by ERED.     

基于路由队列资源自适应的非线性随机早期检测算法

针对随机早期检测(RED)算法在网络拥塞控制中的缺点和复杂性,提出了基于路由队列资源(缓冲)自适应的新算法(ND-RED)。该算法采用非线性丢包策略和动态调整算法参数的方法,使得路由队列长度稳定在参考值附近,从而有效控制了网络拥塞,高效地利用了资源。最后实验结果表明,ND-RED算法具有良好的稳定性,在队列控制和丢包率控制方面优于RED算法。     

Random Early Detection for Congestion Avoidance in Wired Networks: A Discretized Pursuit Learning-Automata-Like Solution

In this paper, we present a learning-automata-like The reason why the mechanism is not a pure LA, but rather why it yet mimics one, will be clarified in the body of this paper. (LAL) mechanism for congestion avoidance in wired networks. Our algorithm, named as LAL Random Early Detection (LALRED), is founded on the principles of the operations of existing RED congestion-avoidance mechanisms, augmented with a LAL philosophy. The primary objective of LALRED is to optimize the value of the average size of the queue used for congestion avoidance and to consequently reduce the total loss of packets at the queue. We attempt to achieve this by stationing a LAL algorithm at the gateways and by discretizing the probabilities of the corresponding actions of the congestion-avoidance algorithm. At every time instant, the LAL scheme, in turn, chooses the action that possesses the maximal ratio between the number of times the chosen action is rewarded and the number of times that it has been chosen. In LALRED, we simultaneously increase the likelihood of the scheme converging to the action, which minimizes the number of packet drops at the gateway. Our approach helps to improve the performance of congestion avoidance by adaptively minimizing the queue-loss rate and the average queue size. Simulation results obtained using NS2 establish the improved performance of LALRED over the traditional RED methods which were chosen as the benchmarks for performance comparison purposes.      

Stability of TCP/RED systems in AQM routers

By applying the time-delay control theory to a TCP/RED dynamic model, this note establishes some explicit conditions under which the TCP/RED system is stable in terms of the average queue length. Then, the stability region is discussed. Finally, the results are illustrated by using ns2 simulations, which demonstrates that it is able to choose an appropriate control parameter max/sub p/ of RED based on the stability conditions derived in this note, to achieve satisfactory network performance. It is found, by comparison, that this improved performance is better than that of three other typical active queue management (AQM) schemes-the random exponential marking (REM), proportional-integral (PI) controller, and adaptive virtual queue (AVQ) schemes.     

Global state feedback stabilisation for a class of high-order nonlinear systems with quantised input and state

In this paper, we aim at addressing the problem of global state feedback stabilisation for a class of high-order nonlinear systems with quantised input and state. The nonlinear functions of the system are bounded by both low-order and high-order terms multiplied by a polynomial-type incremental rate. With the combination of homogeneous domination approach and sector bound approach, a quantised controller computed from quantised state is constructed and a guideline is derived for selecting the parameters of the quantisers. Further, it is proved that, with the proposed scheme, the closed-loop system is globally asymptotically stable.     

Nonlinear System Identification Using Lyapunov Based Fully Tuned Dynamic RBF Networks

This paper presents a stable, on-line identification scheme for multivariable nonlinear dynamic system. Growing Gaussian Radial Basis Function (GRBF) network with all its parameters being adaptable is used to approximate an unknown nonlinear system. Based on a continuous-time framework, the parameter adjustment law is derived using Lyapunov synthesis approach, which guarantees the stability of the overall system. In addition, to ensure the convergence of the approximation error, a growing strategy for the network is selected and a dead zone is incorporated in the tuning law. Simulation studies on identifying a time-varying nonlinear missile dynamics illustrate the superior performance of the proposed scheme. The studies also indicate that stability and reduction in approximation error can be extended to a network with pruning strategy, thereby resulting in a Growing and Pruning (GAP) RBF network, which can implement a more compact network structure.     

A modified L-scheme to solve nonlinear diffusion problems

In this work, we propose a linearization technique for solving nonlinear elliptic partial differential equations that are obtained from the time-discretization of a wide variety of nonlinear parabolic problems. The scheme is inspired by the L-scheme, which gives unconditional convergence of the linear iterations. Here we take advantage of the fact that at a particular time step, the initial guess for the iterations can be taken as the solution of the previous time step. First it is shown for quasilinear equations that have linear diffusivity that the scheme always converges, irrespective of the time step size, the spatial discretization and the degeneracy of the associated functions. Moreover, it is shown that the convergence is linear with convergence rate proportional to the time step size. Next, for the general case it is shown that the scheme converges linearly if the time step size is smaller than a certain threshold which does not depend on the mesh size, and the convergence rate is proportional to the square root of the time step size. Finally numerical results are presented that show that the scheme is at least as fast as the modified Picard scheme, faster than the L-scheme and is more stable than the Newton or the Picard scheme.