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.     

FLRED: an efficient fuzzy logic based network congestion control method

The number of applications running over computer networks has been increasing tremendously, which increased the number of packets running over the network as well leading to resource contention, which ultimately results in congestion. Congestion increases both delay and packet loss while reducing bandwidth utilization and degrading network performance. Network congestion can be controlled by several methods, such as random early detection (RED), which is the most well-known and widely used method to alleviate problems caused by congestion. However, RED and its variants suffer from linearity and parametrization problems. In this paper, we proposed a new method called fuzzy logic RED (FLRED), which extends RED by integrating fuzzy logic to overcome these problems. The proposed FLRED method relies on the average queue length (aql) and the speculated delay (D _Spec ) to predict and avoid congestion at an early stage. A discrete-time queue model is used to simulate and evaluate FLRED. The results showed that FLRED outperformed both RED and effective RED (ERED) by decreasing both delay and packet loss under heavy congestion. Compared with ERED and RED, FLRED decreased the delay by up to 1.5 and 4.5% and reduced packet loss by up to 6 and 30%, respectively, under heavy congestion. These findings suggest that FLRED is a promising congestion method that can save network resources and improve overall performance.

     

Design and analysis of a self-tuning feedback controller for the Internet

Active queue management (AQM) is an effective method used in Internet routers for congestion avoidance, and to achieve a tradeoff between link utilization and delay. The de facto standard, the random early detection (RED) AQM scheme, and most of its variants use average queue length as a congestion indicator to trigger packet dropping. This paper proposes a novel packet dropping scheme, called self-tuning proportional and integral RED (SPI-RED), as an extension of RED. SPI-RED is based on a self-tuning proportional and Integral feedback controller, which considers not only the average queue length at the current time point, but also the past queue lengths during a round-trip time to smooth the impact caused by short-lived traffic dynamics. Furthermore, we give theoretical analysis of the system stability and give guidelines for selection of feedback gains for the TCP/RED system to stabilize the average queue length at a desirable level. The proposed method can also be applied to the other variants of RED. Extensive simulations have been conducted with ns2. The simulation results have demonstrated that the proposed SPI-RED algorithm outperforms the existing AQM schemes in terms of drop probability and stability.     

Reduction of queue oscillation in the next generation Internet routers

The Internet routers employing the random early detection (RED) algorithm for congestion control suffer from the problem of chaotic queue oscillation. It is well known that the slowly varying nature of the average queue size computed using an exponentially weighted moving average (EWMA) used in the RED scheme causes this chaotic behavior. This paper presents a new mathematical function to model the weighting parameter used in the EWMA. The proposed weighting function incorporates the knowledge of the dynamic changes in the congestion characteristics, traffic characteristics and queue normalization. Using this pragmatic information eliminates the slowly varying nature of the average queue size. It is evident from our simulations that the proposed approach not only reduces the chaotic queue oscillation significantly but also provides predictable low delay and low delay jitter with high throughput gain and reduced packet loss rate even under heavy load of traffic conditions.     

改进的随机早期检测非线性算法

主动队列管理是目前的研究热点,随机早期检测(RED)算法是一种经典的队列管理算法。线性RED算法虽然简单且容易计算,但队列位于最小阈值和最大阈值附近时的丢包概率都不太合理。在论证了平均队列长度和丢包概率间为非线性性质后,提出了一种改进非线性RED算法——JRED。利用NS2对改进的算法进行仿真,结果表明,JRED算法提高了平均吞吐量,降低了丢包概率,增强了网络稳定性和可靠性。     

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.     

A novel self-tuning feedback controller for active queue management supporting TCP flows

Wireless access points act as bridges between wireless and wired networks. Since the actually available bandwidth in wireless networks is much smaller than that in wired networks, there is a bandwidth disparity in channel capacity which makes the access point a significant network congestion point. The recently proposed active queue management (AQM) is an effective method used in wired network and wired-wireless network routers for congestion control, and to achieve a tradeoff between channel utilization and delay. The de facto standard, the random early detection (RED) AQM scheme, and most of its variants use average queue length as a congestion indicator to trigger packet dropping. In this paper, we propose a Novel autonomous Proportional and Differential RED algorithm, called NPD-RED, as an extension of RED. NPD-RED is based on a self-tuning feedback proportional and differential controller, which not only considers the instantaneous queue length at the current time point, but also takes into consideration the ratio of the current differential error signal to the buffer size. Furthermore, we give theoretical analysis of the system stability and give guidelines for the selection of feedback gains for the TCP/RED system to stabilize the instantaneous queue length at a desirable level. Extensive simulations have been conducted with ns2. The simulation results have demonstrated that the proposed NPD-RED algorithm outperforms the existing AQM schemes in terms of average queue length, average throughput, and stability.     

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.     

A framework to determine bounds of maximum loss rate parameter of RED queue for next generation routers

Random early detection (RED) is expected to eliminate global synchronization by random active packet drop. Its packet drop probability is decided by the maximum packet drop probability in its drop function, buffer thresholds, and average queue length. It has been observed that for a large number of connections, a small value of the maximum packet drop probability may not eliminate global synchronization. Furthermore, since RED uses four parameters to regulate its performance, it is necessary to relate its maximum drop probability with those parameters. The objective of this paper is to develop a framework for the bounds of the maximum drop probability of RED, based on TCP channel model and traffic characteristics. The value of the maximum drop probability obtained by our model will make RED queue achieve its targeted goals.     

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.      

一种提高稳定性和公平性的主动队列管理机制

结合平均队列和负载衡量拥塞,实现选择性丢包,提出早期选择性丢包算法(ESD)．ESD采用指数函数计算丢包概率,使丢包概率随拥塞程度增大而指数递增;引入记录活跃连接状态信息的虚队列,并在虚队列上假轮转,以检测发送速率大的连接;区分非响应性连接和响应性连接,挑选丢包的候选连接,拥塞时优先丢弃候选连接在队列头部的数据包．实验结果表明,ESD可提高队列稳定性,降低Web流和RTT较大连接的丢包率,提高连接占用带宽的公平性,缩短应用响应时间．     

RED算法的稳定性:基于非线性控制理论的分析

随机旱期检测（Radom Erly Detection,ERD)算法是主动队列管理（ActiveQueue Management,AQM)的有效实现算法，有关它性能的研究是近来网络研究的一个热点，在某些网络配置和负载状态下，RED存在稳定性问题，已有的关于RED稳定性的研究用不同的方法，从不同的角度定性或定量地揭示了可能的原因，并给出了稳定运行的工作区间，但没有对等幅振荡的队列行为给出一个合理的解释，在该文中，作者利用描述函这一非线性控制理论中经典的分析方法，分析了RED和getle-RED的工作特性，认为分组丢弃概率曲线中的非线性结构诱发的自激振荡是队列呈现周期运动的本质原因；虽然相比较而言，getle-RED比RED有更宽的稳定工作区间，但也是非常有限公司，解决AQM稳定性的理想途径是设计更为鲁棒的线性控制器。     

一种改进ARED拥塞控制算法的实现

随着互联网的迅速发展,无论是网民人数还是上网设备数都呈现高速增长的态势。虽然带宽等互联网基础资源相比二十年前有了质的飞跃,但是由于网络规模的增加还是带来了一系列的问题,其中网络拥塞是比较典型的一个。RED作为路由器主动队列管理策略中的重要算法已经在网络拥塞控制方面起到了很好的效果,成为IETF RFC2309建议的唯一候选算法。与队尾丢弃算法DropTail相比,RED算法具有网络链路利用率较高、吞吐量较大、网络时延和丢包率较小的优点,但其存在参数配置无法适应网络动态变化的缺陷,因而改进的ARED算法增加了自适应的功能,但也存在瞬时队列长度振荡等稳定性问题。对此,研究了RED及ARED拥塞控制算法,并提出了一种改进算法QARED,希望通过优化最大丢包概率计算函数来达到提高平均队列长度稳定性以及降低丢包率的目的。     

基于优先级分类的动态随机早期检测队列

针对随机早期检测（RED）算法在服务质量（QoS）保证方面的不足,提出了一种改进队列。该队列基于本地对数据分组的优先级划分,为不同的优先级类别设置不同的RED最大门限值。同时,此系列门限值根据各优先级分组的QoS参数测量值进行动态调整。实验表明,改进的队列继承了RED拥塞控制的优点,提供了一定的QoS保证功能。     

基于RED算法的非线性拥塞控制

由于RED算法是采用丢包率随平均队列长度线性变化的方法,因此导致网络在拥塞并不严重的时候丢包率较大,在拥塞比较严重的时候丢包率较小,拥塞控制能力较低。该文提出非线性平滑算法通过对RED算法的丢包率函数进行非线性平滑,在最小阈值时丢包率增长速度比较小,在最大阈值时丢包率增长速度比较大,有效地控制了平均队列长度,具有较好的拥塞控制能力。NS2仿真结果表明该算法对丢包率、端到端时延、吞吐量以及时延抖动等性能均有较明显的提高。     

A novel numerical algorithm based on self-tuning controller to support TCP flows

Active queue management (AQM) is an effective method used in Internet routers for congestion control, and to achieve a trade off between link utilization and delay. The de facto standard, the random early detection (RED) AQM scheme, and most of its variants use average queue length as a congestion indicator to trigger packet dropping.     

LRED: A Robust and Responsive AQM Algorithm Using Packet Loss Ratio Measurement

Active queue management (AQM) is an effective means to enhance congestion control, and to achieve trade-off between link utilization and delay. The de facto standard, random early detection (RED), and many of its variants employ queue length as a congestion indicator to trigger packet dropping. Despite their simplicity, these approaches often suffer from unstable behaviors in a dynamic network. Adaptive parameter settings, though might solve the problem, remain difficult in such a complex system. Recent proposals based on analytical TCP control and AQM models suggest the use of both queue length and traffic input rate as congestion indicators, which effectively enhances stability. Their response time generally increases however, leading to frequent buffer overflow and emptiness. In this paper, we propose a novel AQM algorithm that achieves fast response time and yet good robustness. The algorithm, called Loss Ratio-based RED (LRED), measures the latest packet loss ratio, and uses it as a complement to queue length for adaptively adjusting the packet drop probability. We develop an analytical model for LRED, which demonstrates that LRED is responsive even if the number of TCP flows and their persisting times vary significantly. It also provides a general guideline for the parameter settings in LRED. The performance of LRED is further examined under various simulated network environments, and compared to existing AQM algorithms. Our simulation results show that, with comparable complexities, LRED achieves shorter response time and higher robustness. More importantly, it trades off the goodput with queue length better than existing algorithms, enabling flexible system configurations     

Dynamic queue level control of TCP/RED systems in AQM routers

One main TCP congestion control objective is, by dynamically adjusting the source window size according to the router queue level, to stabilize the buffer queue length at a given target, thereby achieving predictable queueing delay, reducing packet loss and maximizing link utilization. One difficulty therein is the TCP acknowledging actions will experience a time delay from the router to the source in a TCP system. In this paper, a time-delay control theory is applied to analyze the mechanism of packet-dropping at router and the window-updating in TCP source in TCP congestion control for a TCP/RED dynamic model. We then derive explicit conditions under which the TCP/RED system is asymptotically stable in terms of the instantaneous queue. We discuss the convergence of the buffer queue lengths in the routers. Our results suggest that, if the network parameters satisfy certain conditions, the TCP/RED system is stable and its queue length can converge to any target. We illustrate the theoretical results using ns2 simulations and demonstrate that the network can achieve good performance and converge to the arbitrary target queues.     

基于RED分组丢失历史方法的非TCP流鉴别

随机早期检测(RED)是IETF推荐的一种基于路由器的有效的主动队列管理算法,但是在某些情况下,一些数据量很大的高带宽流量会大量占用带宽,从而导致了各流量之间带宽分配的不公平性,甚至产生拥塞崩溃。该文从RED的丢包历史出发,研究了一种在发生拥塞时鉴别出高带宽流量的方法,并通过仿真证实了此方法的有效性。