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Floyd提出的随机早丢弃(RED,random carly detection)是基于传统的泊松(Possion)模型,不适应网络流量普遍呈现自相似性的特点。基于此目的,提出了一种新的RED算法——Hurst加权随机早检测算法(HWRED,Hurst weighted random early detection)。新算法能够根据输入流量的自相似系数Hurst,调整RED算法参数。仿真结果表明,新算法提高了队列长度的稳定性,减少了丢包率、排队时延和排队抖动,提高了网络的链路利用率。 相似文献
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针对随机早期检测(RED,Random Early Detection)算法存在的公平性问题,提出了一种基于负载的公平性主动队列管理算法(LFED)。该算法通过引入网络负载和队列这两个概念,有效地判断当前网络拥塞程度,同时使用改进的丢包率公式,并且借鉴CHOKe算法的惩罚机制对非响应流进行有效惩罚,以保证不同数据流之间的公平。仿真实验表明,与RED和CHOKe相比,LFED可以得到稳定的瞬时队列长度和减少分组丢弃率,具有较好的公平性和稳定性。 相似文献
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RED算法较好解决了TCP拥塞控制中延迟和长期拥塞问题,但RED算法对参数的设置很敏感,不同的参数设置对RED的性能影响很大。文章就参数的设置提高了RED算法的性能,克服它的一些缺点进行了探讨和研究。 相似文献
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本文在分析RED利用EWMA形式计算平均队列长度的局限性的基础上,提出了一种改进的RED算法。该改进RED算法在计算平均队列长度时考虑了当前队列长度的真实情况,并将两者结合起来进行丢弃决策。仿真结果表明改进RED算法在分组丢弃比例和链路利用率上部优于RED。 相似文献
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AQM(主动队列管理)通过在拥塞的早期阶段丢包来告知信源。AQM改进了响应流(如TCP)和非响应流(如UDP)之间的公平性,它可以带来较高的吞吐量及有效的链路。提出了可变队列长度适应RED算法,它基于每小时的可变队列长度,并且可以更有效地应对突发流。如果将当前可变队列长度与RED及ARED相比,这种方法可以提供更为平缓的平均度列长度。试验结果表明,可变队列长度适应RED比弃尾法提高了公平性,与ARED比较性能也大为改观。这样即使有突发流存在,也可以使数据包稳定地传输。 相似文献
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基于平均队列长度和滞留时间的RED算法 总被引:1,自引:0,他引:1
在无线通信网络环境下,提出了一种改进的基于平均队列长度和滞留时间的RED算法。这种算法根据平均队列长度和滞留时间计算数据包的丢弃概率,比传统的单纯基于平均队列长度的RED算法相比较,能更有效地实现无线网络中的拥塞控制。 相似文献
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本文研究了在ATM交换机上实现的RED算法的性能.在固定有效带宽、时变有效带宽情况下和同种、异种业务环境下,研究了RED算法的通过率、公平性和时延等性能.经研究表明:RED算法有必要与EPD算法相结合,构成RED+EPD算法.采用RED+EPD算法的ATM交换机通过控制平均排队长度,有效地减小了交换机的平均排队时延.通过与其他分组丢弃算法进行性能比较表明:采用RED+EPD算法的ATM交换机,可提供比EPD算法略高的通过率,更好的公平性和更低的排队时延,能较好地支持具有时延要求的业务. 相似文献
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Chengyu Zhu Yang O.W.W. Aweya J. Ouellette M. Montuno D.Y. 《Communications Magazine, IEEE》2002,40(6):158-167
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 相似文献
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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。 相似文献
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Woo-June Kim Byeong Gi Lee 《Electronics letters》1998,34(2):152-154
The authors present the FRED (fair random early detection) algorithm as a congestion control mechanism for TCP over ATM networks. The FRED algorithm enhances the RED gateway algorithm, by using the fact that TCP connections should be allocated buffer space in proportion to their bandwidth-delay products. Through simulation, the effectiveness of the proposed FRED algorithm is shown as compared with the drop-tail and the original RED algorithms 相似文献
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Concerning on the shortcoming and com-plexity of Random early detection (RED) algorithm in net-work congestion control, a new RED algorithm based on the Hemi-Rise Cloud model (CRED) was proposed, non-linear packet loss strategy was used, and sensitivity and un-certainty of parameters were improved. As a result, queue length could be kept stable in the neighborhood of ref-erence value. Network congestion was well controlled and network resource was used effectively. The stability of the algorithm was studied and the experimental results showed that the proposed algorithm could improve the stability, and had better performance than the RED and Adaptive RED (ARED) algorithms. 相似文献
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串联排队RED、ERED网络分析模型 总被引:1,自引:0,他引:1
基于串联排队网络理论,建立了包括多个网络节点的串联排队RED和ERED分析模型。推导了具有指数分布分组丢失函数的RED算法(ERED)。在概率生成函数域,推导了节点的离去过程,并将其拟合为后续节点的到达过程,从而,刻画了多节点级联拥塞控制的通信场景。通过求解串联排队系统,得出串联排队RED、ERED以及DT 3种AQM机制的网络性能指标,分析了AQM参数设置对其性能的影响。针对不同突发度的业务源,给出每个节点和系统端到端性能指标。 相似文献
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Increasing the resolution of an image is an actual and extensively studied problem in image processing. Recently, Regularization by Denoising (RED) showing that any inverse problem can be handled by sequentially applying image denoising steps, including the image super-resolution (SR) task, which facilitate the resolution of the encountered optimization problem. In this paper, we propose a new configuration of genetic algorithms to resolve the super-resolution problem using a Non-Local Means filter as a denoiser function with a rigorous proof of the existence of a unique minimizer. In fact, since the SR algorithms always skip the complex spatial interactions within images, a more consistent model is then needed. The use of the genetic algorithms with the RED techniques guaranteed, in high intensity of noise and blur, the convergence to the globally optimal solution. As a result, the proposed algorithm shows efficient and consistent results, in terms of edges and feature preservation, compared with other SR approaches. 相似文献
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Seyed Saeid Masoumzadeh Kourosh Meshgi Saeid Shiry Ghidari Gelareh Taghizadeh 《International Journal of Network Management》2011,21(2):147-167
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. 相似文献