The BLUE active queue management algorithms

In order to stem the increasing packet loss rates caused by an exponential increase in network traffic, the IETF has been considering the deployment of active queue management techniques such as RED (random early detection) (see Floyd, S. and Jacobson, V., IEEE/ACM Trans. Networking, vol.1, p.397-413, 1993). While active queue management can potentially reduce packet loss rates in the Internet, we show that current techniques are ineffective in preventing high loss rates. The inherent problem with these algorithms is that they use queue lengths as the indicator of the severity of congestion. In light of this observation, a fundamentally different active queue management algorithm, called BLUE, is proposed, implemented and evaluated. BLUE uses packet loss and link idle events to manage congestion. Using both simulation and controlled experiments, BLUE is shown to perform significantly better than RED, both in terms of packet loss rates and buffer size requirements in the network. As an extension to BLUE, a novel technique based on Bloom filters (see Bloom, B., Commun. ACM, vol.13, no.7, p.422-6, 1970) is described for enforcing fairness among a large number of flows. In particular, we propose and evaluate stochastic fair BLUE (SFB), a queue management algorithm which can identify and rate-limit nonresponsive flows using a very small amount of state information.     

Enhanced fuzzy sliding mode controller for active suspension systems

We proposed a fuzzy sliding mode controller (FSMC) to control an active suspension system and evaluated its control performance. The FSMC employed the error of the sprung mass position and the error change to establish a sliding surface, and then introduced the sliding surface and the change of the sliding surface as input variables of a traditional fuzzy controller (TFC) in controlling the suspension system. However, no substantial improvement in the ride comfort could be obtained with the FSMC relative to the TFC because the dynamic effect of the sprung mass acceleration from the bouncing tire during tire rotation was not eliminated. We have developed an enhanced fuzzy sliding mode controller (EFSMC) that maintained not only the original FSMC property but also introduced an assisted FSMC to address and compensate for this problem, and to enhance the road-holding capability of the vehicle. The assisted FSMC differs from the original FSMC only in using the sprung mass acceleration instead of the sprung mass position as a variable of the controller design. The EFSMC exhibits better control performance than either the TFC or the FSMC, in suppressing the acceleration of the vehicle body to improve the ride quality, and in reducing the tire deflection to increase the road-holding ability of a car, as confirmed by experimental results.     

A comparison of active queue management algorithms using the OPNETModeler

A number of active queue management algorithms for TCP/IP networks such as random early detection (RED), stabilized RED (SRED), BLUE, and dynamic RED (DRED) have been proposed in the past few years. This article presents a comparative study of these algorithms using simulations. The evaluation is done using the OPNET Modeler, which provides a convenient and easy-to-use platform for simulating large-scale networks. The performance metrics used in the study are queue size, packet drop probability, and packet loss rate. The study shows that, among the four algorithms, SIZED and DRED are more effective at stabilizing the queue size and controlling the packet loss rate while maintaining high link utilization. The benefits of stabilized queues in a network are high resource utilization, bounded delays, more certain buffer provisioning, and,traffic-load-independent network performance in terms of traffic intensity and number of TCP connections     

基于反步滑模控制的TCP网络的主动队列管理

针对TCP网络的拥塞问题,考虑到网络本身存在参数不确定因素和非响应流的干扰,基于反步滑模控制提出了一种主动队列管理算法。在总的不确定的界已知而且不必很小的情况下,设计了一种反步滑模控制器来补偿系统不确定所带来的影响。仿真结果表明,该方法对TCP网络的复杂变化具有较好的鲁棒性和较快的系统响应。     

REM: active queue management

We describe a new active queue management scheme, random exponential marking (REM), that aims to achieve both high utilization and negligible loss and delay in a simple and scalable manner. The key idea is to decouple the congestion measure from the performance measure such as loss, queue length, or delay. While the congestion measure indicates excess demand for bandwidth and must track the number of users, the performance measure should be stabilized around their targets independent of the number of users. We explain the design rationale behind REM and present simulation results of its performance in wireline and wireless networks     

A genetic algorithm for the design of a fuzzy controller for active queue management

Active queue management (AQM) policies are those policies of router queue management that allow for the detection of network congestion, the notification of such occurrences to the hosts on the network borders, and the adoption of a suitable control policy. This paper proposes the adoption of a fuzzy proportional integral (FPI) controller as an active queue manager for Internet routers. The analytical design of the proposed FPI controller is carried out in analogy with a proportional integral (PI) controller, which recently has been proposed for AQM. A genetic algorithm is proposed for tuning of the FPI controller parameters with respect to optimal disturbance rejection. In the paper the FPI controller design methodology is described and the results of the comparison with random early detection (RED), tail drop, and PI controller are presented.     

一种加强的主动队列管理算法--EBLUE

作为一种典型的主动队列管理算法,BLUE明显不同于其它方法,它使用丢包和连接空闲事件来控制拥塞。试验表明BLUE的丢包率明显小于RED,但是其参数设置仍然存在一些不足之处。本文在BLUE算法的基础之上,通过引进自适应的思想对其进行了改进,提出了一种加强的BLUE队列算法——EBLUE。大量的仿真实验表明本文的改进算法能够进一步提高BLUE的性能。     

自适应模糊滑模控制器设计

针对传统滑模控制的抖振问题,利用线性化反馈技术,将模糊自适应和滑模控制相结合,设计一种新型的模糊滑模控制器。通过模糊推理和基于Lyapunov函数的稳定性分析,获得模糊控制规则的自适应律,构成自适应模糊滑模控制器,有效解决了传统滑模控制中,需要确定参数摄动和外部干扰上确界不确定性问题,倒立摆上的运行结果表明该方法的有效性。     

Signal processing challenges in active queue management

The publication of Floyd and Jacobson's seminal paper "Random early detection gateways for congestion avoidance" (1993), marked a new direction in networking research and began what is perhaps the most investigated example of cross-layer optimization. While this paper has inspired an immense amount of work in research, many open problems in active queue management (AQM) still remain. This article seeks to frame these problems in terms accessible to the signal processing researchers. The basic idea of AQM has been provided as well as its objective and overviews of a sample of different approaches. The signal processing aspects of the AQM are discussed, specifically the problem of predicting congestion, approaches to detecting changes in network traffic, an estimation problem, dithering, and quantization.     

A duality model of TCP and queue management algorithms

We propose a duality model of end-to-end congestion control and apply it to understanding the equilibrium properties of TCP and active queue management schemes. The basic idea is to regard source rates as primal variables and congestion measures as dual variables, and congestion control as a distributed primal-dual algorithm over the Internet to maximize aggregate utility subject to capacity constraints. The primal iteration is carried out by TCP algorithms such as Reno or Vegas, and the dual iteration is carried out by queue management algorithms such as DropTail, RED or REM. We present these algorithms and their generalizations, derive their utility functions, and study their interaction.     

An adaptive virtual queue (AVQ) algorithm for active queue management

Virtual queue-based marking schemes have been recently proposed for Active Queue Management (AQM) in Internet routers. We consider a particular scheme, which we call the Adaptive Virtual Queue (AVQ), and study its following properties: its stability in the presence of feedback delays, its ability to maintain small queue lengths, and its robustness in the presence of extremely short flows (the so-called web mice). Using a linearized model of the system dynamics, we present a simple rule to design the parameters of the AVQ algorithm. We then compare its performance through simulation with several well-known AQM schemes such as RED, REM, Proportional Integral (PI) controller, and a nonadaptive virtual queue algorithm. With a view toward implementation, we show that AVQ can be implemented as a simple token bucket using only a few lines of code.     

队列管理算法对VOIP QoS的提高

VoIP日益成为受用户欢迎的IP网络服务,然而,这些IP网络上的VOIP通话质量却并不能得到令人满意的保证,尤其是当网络拥塞的时候。文中提出了一种不涉及改造网络结构,低成本地提高VOIP的通话质量的方法。通过随机早期检测算法的应用,可以有效地降低VOIP通话的延迟、抖动和有效丢包率,从而提高VOIP的通话质量。     

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。     

A stochastic approximation approach to active queue management

Recently, a dynamic adaptive queue management with random dropping (AQMRD) scheme has been developed to capture the time-dependent variation of average queue size by incorporating the rate of change of average queue size as a parameter. A major issue with AQMRD is the choice of parameters. In this paper, a novel online stochastic approximation based optimization scheme is proposed to dynamically tune the parameters of AQMRD and which is also applicable for other active queue management (AQM) algorithms. Our optimization scheme significantly improves the throughput, average queue size, and loss-rate in relation to other AQM schemes.     

航空发动机模糊滑模变结构控制研究

针对航空发动机是一个具有时变不确定性的非线性系统,结合模糊控制和滑模变结构控制的特点,提出了一种基于模糊滑模变结构控制的航空发动机控制方法.采用线性滑模面和指数趋近律设计变结构控制器,应用模糊逻辑系统自适应调节切换增益,避免了传统滑模变结构控制系统在到达阶段对不确定性的敏感性,消除了滑模控制中的抖振.通过数字仿真,结果表明所设计的模糊滑模变结构控制器对系统的参数摄动和外部干扰具有不变性,使被控系统在整个控制阶段都具有较强的鲁棒性.     

非匹配不确定系统的T-S模糊反演滑模控制

对于一类T-S模糊模型描述的非匹配不确定系统,滑模控制鲁棒性难以保证问题,研究并设计了基于T-S模糊模型的模糊反演控制器。首先中间稳定项通过选择合适的Lyapunov函数来确定,在最后一步中确定滑模控制及参数。逐步设计调节器和跟踪控制器,进而实现系统的全局调节和渐进稳定。从仿真结果可以看出,所设计的模糊反演滑模控制器具有良好的跟踪性能和动态品质,在加入干扰项时,系统仍具有良好的性能,表明该设计控制律的有效性和较强的鲁棒性。     

Adaptive mean queue size and its rate of change: queue management with random dropping

The random early detection active queue management (AQM) scheme uses the average queue size to calculate the dropping probability in terms of minimum and maximum thresholds. The effect of heavy load enhances the frequency of crossing the maximum threshold value resulting in frequent dropping of the packets. An adaptive queue management with random dropping algorithm is proposed which incorporates information not just about the average queue size but also the rate of change of the same. Introducing an adaptively changing threshold level that falls in between lower and upper thresholds, our algorithm demonstrates that these additional features significantly improve the system performance in terms of throughput, average queue size, utilization and queuing delay in relation to the existing AQM algorithms.     

区分服务的改进主动队列管理算法

在区分服务模型中，具有不同微流数量、分组长度和目标速率的流聚集在资源共享时往往无法获得公平带宽。本文在自适应RIO算法基础上提出了一种区分RIO算法（Differentiated RIO，DRIO），DRIO对具有不同目标速率的流区别对待，使得无论在何种情况下都可以很好地保证各流聚集在共享带宽资源上的公平性，而且算法实现简单。仿真结果表明，DRIO对提高流聚集之间的公平性有很明显的效果。