A Fully Adaptive Active Queue Management Method for Congestion Prevention at the Router Buffer

Active queue management(AQM)methods manage the queued packets at the router buffer,prevent buffer congestion,and stabilize the network performance.The bursty nature of the traffic passing by the network routers and the slake behavior of the existing AQM methods leads to unnecessary packet dropping.This paper proposes a fully adaptive active queue management(AAQM)method to maintain stable network performance,avoid congestion and packet loss,and eliminate unnecessary packet dropping.The proposed AAQM method is based on load and queue length indicators and uses an adaptive mechanism to adjust the dropping probability based on the buffer status.The proposed AAQM method adapts to single and multiclass traffic models.Extensive simulation results over two types of traffic showed that the proposed method achieved the best results compared to the existing methods,including Random Early Detection(RED),BLUE,Effective RED(ERED),Fuzzy RED(FRED),Fuzzy Gentle RED(FGRED),and Fuzzy BLUE(FBLUE).The proposed and compared methods achieved similar results with low or moderate traffic load.However,under high traffic load,the proposed AAQM method achieved the best rate of zero loss,similar to BLUE,compared to 0.01 for RED,0.27 for ERED,0.04 for FRED,0.12 for FGRED,and 0.44 for FBLUE.For throughput,the proposed AAQM method achieved the highest rate of 0.54,surpassing the BLUE method’s throughput of 0.43.For delay,the proposed AAQM method achieved the second-best delay of 28.51,while the BLUE method achieved the best delay of 13.18;however,the BLUE results are insufficient because of the low throughput.Consequently,the proposed AAQM method outperformed the compared methods with its superior throughput and acceptable delay.

Active Queue Management技术的研究与发展

Active Queue Management(AQM)技术通过有效控制输出队列的丢包时间和丢包方式,对拥塞进行早期通告,这在TCP拥塞控制的实现中至关重要。目前对AQM进行较全面介绍和总结的文献尚不多见,以RandomEarly Detection(RED)为重点介绍了这种第一代AQM技术的设计思想、优缺点以及为此出现的多种RED变种方法,另外还简单介绍了其它几种与RED设计思路不同的AQM方法,以期对AQM技术的研究和发展进行较全面的总结,并促进国内学者以及设备制造商对这一技术的关注。

An Active Queue Management Algorithm: CRED

By applying the method of average and variance, a new queue management algorithm named the Classified-Random Early Detection （CRED） algorithm is presented which can identify the media streaming, TCP traffic and other UDP traffic at the edge routers. The algorithm discriminates the slow start and the congestion control phase of the TCP traffic and combines the TCP congestion control with the IP congestion control to alleviate the congestion effectively. Simulation shows that CRED can not only make the media streaming obtain the resources needed but also protect the TCP traffic transmitted effectively and reliably.

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 pre- dominance 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. Theo- retical 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.

Active Queue Management Exploiting the Rate Information in TCP-IP Networks

In this paper, we propose a new mechanism called explicit rate notification(ERN) to be used in end-to-end communications. The ERN scheme encodes in the header of transmission control protocol(TCP) packets information about the sending rate and the round trip time(RTT) of the flows. This new available information to the intermediate nodes(routers) is used to improve fairness, increase utilization, decrease the number of drops, and minimize queueing delays. Thus, it induces a better management of the queue. A comparison of our scheme with preexistent schemes, like the explicit congestion notification scheme, shows the effectiveness of the proposed mechanism.

Fuzzy variable structure algorithms for active queue management with delay compensation

Based on the linearized model of the TCP connections through the congested routers, this paper puts forward an active queue management algorithm (FVS-T). The algorithm utilizes the fuzzy variable structure control algorithm with delay factor to compensate time varying round-trip times (RTT) and uncertainties with respect to the number of active TCP sessions. By analyzing the robustness and performance of the control scheme for the nonlinear TCP/AQM model, we show that the proposed design has good performance and robustness, which are central to the notion of AQM. Implementation issues were discussed and ns simulations were provided to validate the design and compare its performance to other peer schemes in different scenarios. The results show that the proposed design significantly outperforms the other congestion schemes in terms of packet loss ratio, throughput and buffer fluctuation.

A Robust Algorithm in Active Queue Management

A variable structure based control scheme was proposed for Active Queue Management(AQM) by using sliding model algorithm and reach law method. This approach aims to address the tradeoff between good performance and robustness with respect to the uncertainties of the round-trip time and the number of active connections. Ns simulations results show that the proposed design significantly outperforms the peer AQM schemes in terms of fluctuation in the queue length, packet throughput, and loss ratio. The conclusion is that proposed scheme is in favor of the achievement to AQM objectives due to its good transient and steady performance.

Multi-indicator Active Queue Management Method

A considerable number of applications are running over IP networks.This increased the contention on the network resource,which ultimately results in congestion.Active queue management(AQM)aims to reduce the serious consequences of network congestion in the router buffer and its negative effects on network performance.AQM methods implement different techniques in accordance with congestion indicators,such as queue length and average queue length.The performance of the network is evaluated using delay,loss,and throughput.The gap between congestion indicators and network performance measurements leads to the decline in network performance.In this study,delay and loss predictions are used as congestion indicators in a novel stochastic approach for AQM.The proposed method estimates the congestion in the router buffer and then uses the indicators to calculate the dropping probability,which is responsible for managing the router buffer.The experimental results,based on two sets of experiments,have shown that the proposed method outperformed the existing benchmark algorithms including RED,ERED and BLUE algorithms.For instance,in the first experiment,the proposed method resides in the third-place in terms of delay when compared to the benchmark algorithms.In addition,the proposed method outperformed the benchmark algorithms in terms of packet loss,packet dropping,and packet retransmission.Overall,the proposed method outperformed the benchmark algorithms because it preserves packet loss while maintaining reasonable queuing delay.

RED-DTB: A Dual Token Bucket Based Queue Management Algorithm

Improving the Quality of Service (QoS) of Internet traffic is widely recognized as a critical issue for the next-generation networks. In this paper, we present a new algorithm for the active queue management, namely RED-DTB. This buffer control technique is used to enforce approximate fairness among a large number of concurrent Internet flows. Like RED (Random Early Detection) algorithm, the RED-DTB mechanism can be deployed to actively respond to the gateway congestion, keep the gateway in a healthy state, and protect the fragile flows from being stolen bandwidth by greedy ones. The algorithm is based on the so-called Dual Token Bucket (DTB) pattern. That is, on the one hand, every flow is rate-limited by its own token bucket, to ensure that it can not consume more than its fair share of bandwidth; On the other hand, to make some compensations to less aggressive flows, such as connections with larger round trip time or smaller sending window, and to gain a relatively higher system utilization coefficient, all flows, depending on their individual behavior, may have a chance to fetch tokens from the public token bucket when they run out of their own share of tokens. The algorithm is analyzed and evaluated by simulations, and is proved to be effective in protecting the gateway buffer and controlling the fair allocation of bandwidth among flows.

基于AQM算法的通信电源智能管理系统设计

在现代通信系统中,电源管理的效率和智能化水平直接影响到系统的稳定性和能效。主动队列管理(Active Queue Management,AQM)算法作为一种先进的网络数据流控制技术,通过动态调整队列的行为来优化数据传输和降低延迟。该算法主要用于改善网络拥塞,但近年来被引入通信电源管理,用于优化电源的分配和使用,增强系统的响应能力和效率。文章设计一个基于AQM算法的通信电源智能管理系统,详细阐述系统的需求、架构设计以及模块划分,并通过系统集成与应用测试验证设计的有效性。通过引入AQM算法,设计系统能够实现电源管理的动态优化,从而提升整个通信系统的性能和可靠性。

Traffic Queuing Management in the Internet of Things: An Optimized RED Algorithm Based Approach

Congestion control is one of the main obstacles in cyberspace traffic.Overcrowding in internet traffic may cause several problems;such as high packet hold-up,high packet dropping,and low packet output.In the course of data transmission for various applications in the Internet of things,such problems are usually generated relative to the input.To tackle such problems,this paper presents an analytical model using an optimized Random Early Detection(RED)algorithm-based approach for internet traffic management.The validity of the proposed model is checked through extensive simulation-based experiments.An analysis is observed for different functions on internet traffic.Four performance metrics are taken into consideration,namely,the possibility of packet loss,throughput,mean queue length and mean queue delay.Three sets of experiments are observed with varying simulation results.The experiments are thoroughly analyzed and the best packet dropping operation with minimum packet loss is identified using the proposed model.

COCM: Class Based Optimized Congestion Management Protocol for Healthcare Wireless Sensor Networks

Wireless Sensor Networks (WSNs) consist of numerous sensor nodes which can be used in many new emerging applications like healthcare. One of the major challenges in healthcare environments is to manage congestion, because in applications, such as medical emergencies or patients remote monitoring, transmitted data is important and critical. So it is essential in the first place to avoid congestion as much as possible and in cases when congestion avoidance is not possible, to control the congestion. In this paper, a class based congestion management protocol has been proposed for healthcare applications. We distinguish between sensitive, non-sensitive and control traffics, and service the input traffics based on their priority and quality of service requirements (QoS). The proposed protocol which is called COCM avoids congestion in the first step using multipath routing. The proposed AQM algorithm uses separate virtual queue's condition on a single physical queue to accept or drop the incoming packets. In cases where input traffic rate increases and congestion cannot be avoided, it mitigates congestion by using an optimized congestion control algorithm. This paper deals with parameters like end to end delay, packet loss, energy consumption, lifetime and fairness which are important in healthcare applications. The performance of COCM was evaluated using the OPNET simulator. Simulation results indicated that COCM achieves its goals.

一种ICN流量区分的AQM算法

信息中心网络(ICN)是一种满足海量内容的数据分发需求的新型网络架构。在ICN中,用户向网络发送请求报文,网络中的缓存副本节点则会响应请求回复数据报文。请求报文与数据报文的流量是ICN中2种截然不同的流量类型。在网络发生拥塞时,为保证传输效率,需要区分处理不同特点的流量。针对ICN网络的延迟保障与带宽利用率问题,提出了一种区分报文类型的主动队列管理AQM算法。该算法通过对2种流量执行主动丢包操作,使2种流量趋于一个合理的状态。基于对2种流量被主动丢包的概率根据统计的2种报文流量占用带宽的大小结合比例积分控制器计算得出。同时,通过报文调度器优先调度对请求报文减少数据传输的往返时间。实验表明,提出的AQM算法能够合理分配2种报文占用的带宽,提高网络严重拥塞时数据传输的吞吐量,减少完成时间,降低往返时间。

基于流量自相似性的网络队列管理算法

网络流量的自相似性会导致数据突发状态持续,传统队列管理算法无法对网络流量突发状态进行预测,从而影响网络端到端时延、丢包率和吞吐性能。针对该问题,提出一种基于网络流量预测的主动队列管理算法P-ARED。基于网络流量的均值和方差给出网络流量等级的概念,讨论网络流量等级转移概率与Hurst参数之间的关系,提出基于贝叶斯估计思想的网络流量等级预测方法。在此基础上,在对自相似网络流量环境下的平均队列长度、缓存队列长度最小阈值等参数优化设置的基础上,基于Hurst参数和自相似流量等级预测结果,重新设计ARED算法中分组丢弃概率的计算方法,以提高缓存队列长度的稳定性。仿真结果表明,P-ARED算法与对比的主动队列管理算法相比,降低了网络端到端时延和丢包率,提高了端到端吞吐性能,其中平均吞吐量最高提升7.63%,平均时延最多降低17.52%。

Design and Analysis of a Multiscale Active Queue Management Scheme

Since Internet is dominated by TCP-based applications, active queue management （AQM） is considered as an effective way for congestion control. However, most AQM schemes suffer obvious performance degradation with dynamic traffic. Extensive measurements found that Internet traffic is extremely bursty and possibly self-similar. We propose in this paper a new AQM scheme called multiscale controller （MSC） based on the understanding of traffic burstiness in multiple time scale. Different from most of other AQM schemes, MSC combines rate-based and queue-based control in two time scales. While the rate-based dropping on burst level （large time scales） determines the packet drop aggressiveness and is responsible for low and stable queuing delay, good robustness and responsiveness, the queue-based modulation of the packet drop probability on packet level （small time scales） will bring low loss and high throughput. Stability analysis is performed based on a fluid-flow model of the TCP/MSC congestion control system and simulation results show that MSC outperforms many of the current AQM schemes.

不确定时滞TCP/AQM系统的滑模控制

针对具有非匹配不确定项和输入时滞的TCP线性化动态系统进行特殊线性变换,将原不确定时滞系统转化为无时滞系统.在新坐标下,基于滑模控制(SMC)设计了一种主动队列管理(AQM)算法.根据滑模到达条件设计了一种控制策略,基于LMI技术给出线性滑动超平面的设计方法,通过Lyapunov函数证明了系统的稳定性.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,尤其是在网络条件变化的情况下,该方法优于传统的滑模控制,能实现准确的跟踪,具有良好的鲁棒性.

SABlue:一种带加速因子的自适应AQM算法

该文在分析SBlue算法的基础上,提出了一种带加速因子的自适应AQM算法SABlue(Self-tune AccelerateBlue)。算法将瞬时队长作为早期拥塞检测参量,根据队列负载因子控制丢包步长,实现丢包概率幅度的自适应调整,最终将路由队列长度稳定在目标区域内。为了提高网络突变跨度较大情况时算法的响应速度,在队列警戒区域内引入了加速因子。实验表明,SABlue面对突变流和不同RTT的网络场景,队列收敛时间短,丢包率小,且具有较好的鲁棒性,算法综合性能优于其他AQM算法。

一种新的快速响应的AQM算法

该文应用控制理论,设计了具有快速响应特征的比例积分(Proportional-Integral,PI)控制器,并以此提出了一个新的主动队列管理(Active Queue Management,AQM)算法,称为ActivePI算法(简称A-PI)。A-PI用一组参数实现快速响应,用另一组参数保证队长稳定,使用门限值实现两组参数间平滑切换,算法实现简单。理论分析和仿真实验表明,A-PI算法在保证队长稳定的同时实现了对不同网络环境的快速响应。

基于增益自适应Smith预估器的鲁棒AQM拥塞控制算法

根据Lyapunov渐近稳定定理,提出了一种基于增益自适应Sm ith预估器的鲁棒主动队列管理(AQM)拥塞控制算法(GAS-PI).该算法结构简单,具有良好的鲁棒性和网络控制性能,同时克服了大时滞给队列稳定性造成的不利影响.仿真结果表明:采用GAS-PI算法,对于限制系统振荡超调量的作用非常明显,同时能使网络具有更快的响应速度及更平稳的队列———在HTTP扰动和负载变动较大的情况下,算法使得缓存队列迅速收敛到稳定值;当网络时延增大时,算法能使网络的动态性能依然保持良好.

自相似网络流量可预测性及其在AQM中的应用

从网络流量的自相似性带来的可预测性入手,小结了两类常用的预测方法,并对其进行了比较;然后根据已有预测算法,将预测结果引入经典主动队列管理机制——RED算法中,提出了基于流量预测的RED算法;最后通过仿真实验表明,该算法能较好地控制平均队列长度,提高主动队列管理的性能。