Nonlinear performance evaluation model for throughput of AQM scheme using full factorial design approach

The performance of active queue management (AQM) is measured in terms of throughput, delay, queue size, and loss rate. We have carried out the optimized performance measure of throughput for AQM scheme random early detection (RED) using full factorial design (FDD) technique that is a new approach of performance analysis particularly for congestion control algorithms. We have considered the input factors, viz, buffer size, maximum threshold, and the number of file transfer protocol (FTP) sources for the evaluation of RED that can be used for other AQM schemes, viz, adaptive RED, three‐section RED (TRED), and adaptive queue management with random dropping (AQMRD). The effect of each input factor as well as their interactions are evaluated using factorial design technique that results to obtain the nonlinear equation for performance measure in terms of input factors buffer size, maximum threshold, and the number of FTP sources. Finally, we show the contour plots for variation of performance measure throughput (steady state) from minimum to maximum values with respect to the different setting of input parameters.     

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.     

Advances in internet congestion control

In this survey, we first review the concept of congestion control with a focus on the Transmission Control Protocol⁄Internet Protocol (TCP⁄IP). We describe many recently proposed algorithms to combat congestion and improve performance, particularly active queue management (AQM) algorithms such as random early detection (RED) and its variants. We then survey control-theoretic analysis and design of TCP congestion control with an AQM scheme. In addition, we discuss three problems associated with AQM proposals: parameter setting, the insensitivity to the input traffic load variation, and the mismatch between macroscopic and microscopic behavior of queue length dynamics. As alternatives to AQM algorithms, we also survey architectural approaches such as modification of source or network algorithms, and economic approaches including pricing or optimization of allocated resources. Finally, we list many open issues that persist in the design, operation, and control of the Internet.     

PD-RED: to improve the performance of RED

We propose a new active queue management (AQM) scheme to improve the performance of the well-known random early detection (RED) AQM. The new AQM is based on the proportional derivative (PD) control principle, and we call it PD-RED. In PD-RED we introduce minimal changes to RED. We demonstrate the improvement in performance of PD-RED over adaptive RED AQM by simulations.     

Rate‐based proportional–integral control scheme for active queue management

Most high‐speed links do not have adequate buffering and as a result Active Queue Management (AQM) schemes that utilize queue size information for congestion control cannot be effectively applied on these links. A high‐speed link will, typically, have small buffers in relation to the bandwidth‐delay product of the link. In this paper we argue that rate‐based AQM schemes be used for such links. The goal here is to match the aggregate rate of the active TCP connections to the available capacity while maintaining minimal queue size and high link utilization. The AQM scheme described here employs a Proportional–Integral (PI) control strategy and explicitly takes into account the time delay in the control process. Copyright © 2006 John Wiley & Sons, Ltd.     

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。     

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.     

Relative loss rate differentiation: performance of short‐lived TCP flows

The relative differentiated service model provides assurances for the relative quality ordering between service classes, rather than for the actual service level in each class. In this paper, we describe a relative loss rate differentiation scheme where packet drop probabilities are determined according to an active queue management (AQM) mechanism based on random early detection (RED) in a first‐in first‐out (FIFO) queue, are weighted in inverse proportion to the price that the network operator assigns to each service class. Basically, we describe a scheme where relative loss rate differentiation is incorporated directly into AQM. Most TCP flows today, particularly Web flows, can be characterized as short‐lived flows. Using simulations with short‐lived TCP flows, we show that the scheme is very effective in ensuring relative loss rate differentiation between service classes during times of network congestion. Copyright © 2004 John Wiley & Sons, Ltd.     

主动队列管理机制在无线系统中的优化

主动队列管理(AQM)是对抗拥塞的重要手段,其经典算法之一是随机早期丢弃,简称RED。为使其能适应无线传输高突发误帧的特点,本文提出了一种基于平均队列长度和平均包到达速率的改进RED算法,分析了其相对于传统RED算法在预防和处理拥塞时的优势。同时针对无线信道的时变特性,提出自适应MIR速率调整,以提高频谱利用率和进一步降低拥塞概率,并讨论了其对于系统性能的改善。     

A novel AQM algorithm based on feedforward model predictive control

Developing feedforward model predictive controller as an active queue management (AQM) scheme is studied in this paper. MPC is an advanced control strategy for AQM. However, the conventional MPC is usually an implementable form of feedback MPC. In this paper, a feedforward and feedback optimal control law is presented. It is a clean, easily implementable, version of model predictive control that incorporates feedforward. Firstly, we use the nominal fluid model to design the feedforward control input so that the output tracks the given queue length with small error. Furthermore, in order to achieve robust performance and to reject the (unmeasured) disturbance, the feedback component is designed. In particular, a disturbance observer is incorporated into the prediction output in standard feedback MPC. This framework can significantly improve performance in the presence of measurement noise and certain types of model uncertainty. Finally, the simulation results show the effectiveness of FF‐AQM algorithm.     

A novel adaptive traffic prediction AQM algorithm

In the Internet, network congestion is becoming an intractable problem. Congestion results in longer delay, drastic jitter and excessive packet losses. As a result, quality of service (QoS) of networks deteriorates, and then the quality of experience (QoE) perceived by end users will not be satisfied. As a powerful supplement of transport layer (i.e. TCP) congestion control, active queue management (AQM) compensates the deficiency of TCP in congestion control. In this paper, a novel adaptive traffic prediction AQM (ATPAQM) algorithm is proposed. ATPAQM operates in two granularities. In coarse granularity, on one hand, it adopts an improved Kalman filtering model to predict traffic; on the other hand, it calculates average packet loss ratio (PLR) every prediction interval. In fine granularity, upon receiving a packet, it regulates packet dropping probability according to the calculated average PLR. Simulation results show that ATPAQM algorithm outperforms other algorithms in queue stability, packet loss ratio and link utilization.     

Virtual rate control algorithm for active queue management in TCPnetworks

A virtual rate control (VRC) algorithm for active queue management (AQM) to regulate the queue length with small variation and to achieve high utilisation with small packet loss is proposed. Through ns simulations, the effectiveness of the proposed VRC algorithm as compared with several well-known AQM schemes such as random early detection (RED), random exponential marking (REM), and adaptive virtual queue (AVQ) algorithms is shown     

几种主动式队列管理算法的比较研究

主动式队列管理(Active Queue Management,AQM)技术是IETF为了解决Internet拥塞控制问题而提出的一种路由器缓存管理技术.本文对几种主要AQM算法RED、BLUE、ARED和SRED的性能在基于ns-2仿真实验的基础上进行了比较研究.研究的性能包括队列长度、丢包概率、丢包率、连接数对吞吐量的影响及缓冲区大小对链路利用率的影响等.仿真结果表明BLUE、ARED和SRED在这几方面的性能都要优于RED算法.     

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.     

Advances in Active Queue Management (AQM) Based TCP Congestion Control

Current end-to-end Internet congestion control under tail-drop (TD) queue management experiences performance degradations such as multiple packet losses, high queueing delay and low link utilization. In this paper, we review recently proposed active queue management (AQM) algorithms for supporting end-to-end transmission control protocol (TCP) congestion control. We focus recently developed control theoretic design and analysis method for the AQM based TCP congestion control dynamics. In this context, we analyze the problems of existing AQM proposals in which congestion is detected and controlled reactively based on current and/or past congestion. Then we argue that AQM based TCP congestion control should be adaptive to the dynamically changing traffic situation in order to detect, control and avoid the current and the incipient congestion proactively. Finally, we survey two adaptive and proactive AQM algorithms, PID-controller and Pro-Active Queue Management (PAQM), designed using classical proportional-integral–derivative (PID) feedback control to overcome the reactive congestion control dynamics of existing AQM algorithms. A comparative study of these AQM algorithms with existing AQM algorithms is given. A simulation study under a wide range of realistic traffic conditions suggests that PID-controller and PAQM outperform other AQM algorithms such as random early detection (RED) [Floyd and Jacobson, 18] and proportional-integral (PI) controller [Hollot et al., 24].     

FQL‐RED: an adaptive scalable schema for active queue management

In a potentially congested network, random early detection (RED) active queue management (AQM) proved effective in improving throughput and average queuing delay. The main disadvantage of RED is its sensitive parameters that are impossible to estimate perfectly and adjust manually because of the dynamic nature of the network. For this reason, RED performs differently during different phases of a scenario and there is no guarantee that it will have optimal performance. Giving adaptability to RED has been the subject of broad research studies ever since RED was proposed. After a substantial study of AQM schemes and presenting a novel categorization for so‐called modern approaches utilizing artificial intelligence tools to improve AQM, this paper proposes an algorithm enhancing RED as an add‐on patch that makes minimal changes to the original RED. Being built on the basis of AQM schemes like ARED and Fuzzy‐RED, this algorithm inherits adaptability and is able to adjust RED inaccurate parameters regarding network traffic status, trying to optimize throughput and average queuing delay in a scenario. This algorithm is a Q‐learning method enhanced with a fuzzy inference system to provide RED with self‐adaptation and improved performance as a result. Given the name of FQL‐RED, this algorithm outperformed RED, ARED, and Fuzzy‐RED, as the OPNET simulations show. Copyright © 2010 John Wiley & Sons, Ltd.     

Proxy‐RED: an AQM scheme for wireless local area networks

Wireless access points (APs) act as bridges between wired and wireless networks. Since the actually available bandwidth in wireless networks is much smaller than the bandwidth in wired networks, there is a disparity in channel capacity which makes the access point a significant network congestion point in the downstream direction. A current architectural trend in wireless local area networks (WLAN) is to move functionality from APs to a centralized gateway in order to reduce cost and improve features. In this paper, we study the use of RED, a well known active queue management (AQM) scheme, and explicit congestion notification (ECN) to handle bandwidth disparity between the wired and the wireless interface of an access point. Then, we propose the Proxy‐RED scheme, as a solution for reducing the AQM overhead from the access point. Simulations‐based performance analysis indicates that the proposed Proxy‐RED scheme improves the overall performance of a network. In particular, the Proxy‐RED scheme significantly reduces packet loss rate and improves goodput for a small buffer, and minimizes delay for a large buffer size. Copyright © 2006 John Wiley & Sons, Ltd.     

Adaptive AQM controllers for IP routers with a heuristic monitor on TCP flows

We propose adaptive proportional (P) and proportional‐integral (PI) controllers for Active Queue Management (AQM) in the Internet. We apply the classical control theory in the controller design and choose a proper phase margin to achieve good performance of AQM. We have identified a simple heuristic parameter that can monitor the changes of network environment. Our adaptive controllers would self‐tune only when the dramatic change in the network parameters drift the monitoring parameter outside its specified interval. When compared to P controller, a PI controller has the advantage of regulating the TCP source window size by adjusting the packet drop probability based on the knowledge of instantaneous queue size, thus steadying the queue size around a target buffer occupancy. We have verified our controllers by OPNET simulation, and shown that with an adaptive PI controller applied, the network is asymptotically stable with good robustness. Copyright © 2005 John Wiley & Sons, Ltd.     

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 novel Markov analytical model for the TCP/AQM systems

A novel closed-loop feedback TCP/AQM(Transfer Control Protocol/Active Queue Management) model is proposed in this paper using a discrete-time Markov chain,and a way to calculate the equilibrium distribution of this model is given.In the model,system time is divided into time slots,the bottleneck router queue model and TCP window size model in each slot are analyzed.Finally,by combining adjacent slots,an integrated TCP/AQM analytical model is developed.By this model,the average values of packets dropping rat...