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 Accelerate Blue)。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。     

一种新的基于网络丢包率的主动队列管理策略

提出了一种新的基于网络丢包率的动态自适应的主动队列管理的改进算法。该算法首先用早期网络的丢包率标记到达的数据包,并作为数据包的丢弃概率。这样使得到达数据包的丢弃概率逼近当前实际网络的丢包率,然后经过自适应调整丢弃概率使得缓冲队列长度保持在一定范围内。通过NS仿真实验表明了该算法可以很好的控制队列长度,降低延迟抖动。     

DRED: a random early detection algorithm for TCP/IP networks

It is now widely accepted that a RED [2] controlled queue certainly performs better than a drop‐tail queue. But an inherent weakness of RED is that its equilibrium queue length cannot be maintained at a preset value independent of the number of TCP active connections. In addition, RED's optimal parameter setting is largely correlated with the number of connections, the round‐trip time, the buffer space, etc. In light of these observations, we propose DRED, a novel algorithm which uses the basic ideas of feedback control to randomly discard packets with a load‐dependent probability when a buffer in a router gets congested. Over a wide range of load levels, DRED is able to stabilize a router queue occupancy at a level independent of the number of active TCP connections. The benefits of stabilized queues in a network are high resources utilization, predictable maximum delays, more certain buffer provisioning, and traffic‐load‐independent network performance in terms of traffic intensity and number of connections. Copyright © 2002 John Wiley & Sons, Ltd.     

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     

主动队列管理算法的分类器实现

作为端到端拥塞控制的增强机制,主动队列管理(AQM)通过在网络中间节点有目的地丢弃分组来维持较小的队列长度和较高的链路利用率.已有的大多数主动队列管理算法沿用了随机早期探测(RED)算法首创的概率丢弃机制.本质上,判决是否丢弃分组的过程是一个依赖于网络拥塞状态的决策过程,因此,概率决策不应该是唯一的方法.在本文的研究中,我们首先归纳了理想AQM算法所应具备的品质,然后应用模式识别中分类器的设计思想提出了一种新颖简洁的主动队列管理策略实现框架,并基于Fisher线性判别方法为AQM设计了一个两维两类分类器(TCC).仿真试验表明TCC有效、敏捷、鲁棒,扩展性好,同时实现简单,计算开销小,有利于高速路由器的性能优化.     

一种基于模糊逻辑的主动队列管理算法

主动队列管理 (ActiveQueueManagement,AQM)技术作为Internet拥塞控制的一种有效方法 ,对于提高In ternet的服务质量具有十分重要的作用 .本文根据TCP拥塞控制算法基于数据包丢失的窗口变化机制 ,设计了一种基于模糊逻辑的主动队列管理算法 .该算法依据路由器中队列长度的变化情况 ,根据一定的模糊自校正原则来调整数据包的丢弃概率 ,从而使路由器中的队列长度稳定在参考值附近 .仿真结果表明该算法不但十分有效 ,而且对不同的网络状况具有很好的适应能力 .     

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.     

一种顽健的自校正主动队列管理机制

现有基于控制理论的主动队列管理机制（AQM）大多数是根据简化的线性被控对象模型设计的,或者根据特定的网络条件设置算法的参数,当网络条件大范围变化时算法的性能难以保证.为了解决这些问题,提出了一种自校正的主动队列管理机制STR,通过在线估计TCP/AQM闭环系统被控对象模型的参数,并相应地调节报文丢弃概率,使路由器的缓冲区队列长度与期望值之间的方差最小.通过仿真实验验证了当网络条件大范围变化时算法的队列长度、链路利用率、报文丢弃率等性能,实验结果表明该算法具有良好的顽健性.     

Using interval phase margin assignment to self-tune a PI AQM controller for TCP traffic

We propose a self-tuning PI (Proportional-Integral) controller for an AQM (Active Queue Management) router supporting TCP traffic in the Internet. Classical control theory is applied in the controller design to meet the phase margin specification in the frequency domain. By assigning a proper interval of the phase margin, we can achieve good AQM performance by making the control system adapt to dramatic load changes. Our self-tuning PI controller self-tunes only when there is a great change in the network environment that would cause the phase margin of the AQM control system to drift outside the specified interval. Based on the knowledge of the queue size, our PI controller can regulate the TCP source window size by adjusting the packet drop probability, thus clamping the steady queue size around a desirable target buffer occupancy. We demonstrate by OPNET^® simulations that with our self-tuning PI controller applied, the network exhibits a good transient behavior. A simple PID (Proportional-Integral-Derivative) controller design method is also provided.     

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.     

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.     

A simple mechanism for stabilizing network queues in TCP/IP networks

In this paper we determine the stability bounds for the DRED active queue management (AQM) algorithm using a previously developed nonlinear dynamic model of TCP. We develop a second‐order linear model with time delay by linearizing the nonlinear model. Using the Pade approximation of time‐delayed system e^?R0s, where R₀ is the delay in the system, we then determine the range of stabilizing gains of DRED when controlling the second‐order system with time delay R₀. We also present examples showing the stability bounds of the DRED controller gain for networks with different parameters such as link capacity, load level, and round‐trip time. In addition, we describe an efficient implementation of the DRED AQM algorithm. Copyright © 2006 John Wiley & Sons, Ltd.     

A compensated PID active queue management controller using an improved queue dynamic model

Beside the major objective of providing congestion control, achieving predictable queuing delay, maximizing link utilization, and robustness are the main objectives of an active queue management (AQM) controller. This paper proposes an improved queue dynamic model while incorporating the packet drop probability as well. By applying the improved model, a new compensated PID AQM controller is developed for Transmission Control Protocol/Internet Protocol (TCP/IP) networks. The non‐minimum phase characteristic caused by Padé approximation of the network delay restricts the direct application of control methods because of the unstable internal dynamics. In this paper, a parameter‐varying dynamic compensator, which operates on tracking error and internal dynamics, is proposed to not only capture the unstable internal dynamics but also reduce the effect of uncertainties by unresponsive flows. The proposed dynamic compensator is then used to design a PID AQM controller whose gains are obtained directly from the state‐space representation of the system with no further gain tuning requirements. The packet‐level simulations using network simulator (ns2) show the outperformance of the developed controller for both queuing delay stability and resource utilization. The improved underlying model leads also to the faster response of the controller. Copyright © 2013 John Wiley & Sons, Ltd.     

主动队列管理算法性能评价：比较研究

对当前的主动队列管理算法进行了分类，然后基于NS2网络仿真器比较了它们在不同流量和网络拓扑条件下的多种性能指标。主要结论包括：ARED综合表现最好；PI和REM的瞬态性能较差，对动态流量响应较慢：REM和没有ECN支持的AVQ可以得到较小的时延，但同时牺牲了链路的带宽利用率并造成大量分组丢失；在多瓶颈网络拓扑中，大部分算法的性能有所提高。     

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.     

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.     

无线链路多用户视频流传输QoS保证：延时限制及优先级丢包

To provide a certain level of Quality of Service (QoS) guarantees for multiuser wire-less downlink video streaming transmissions, we propose a multiuser scheduling scheme for QoS guarantees. It is based on the classic Queue-Length-Based (QLB)-rate maximum scheduling algorithm and integrated with the delay constraint and the packet priority drop. We use the large deviation principle and the effective capacity theory to construct a new analysis model to find each user’s queue leng-th threshold (delay constraint) violation prob-ability. This probability corresponds to the upper bound of the packet drop probability, which indicates a certain level of statistical QoS guarantees. Then, we utilize the priority information of video packets and introduce the packet priority drop to further improve the quality perceived by each user. The simu-lation results show that the average Peak Signal to Noise Ratio (PSNR) value of the priority drop is 0.8 higher than that of the non-priority drop and the PSNR value of the most badly damaged video frame in the priority drop is on an average 4 higher than that of the non-priority drop.     

一种时滞网络自适应主动队列管理算法研究

主动队列管理(AQM)算法的自适应能力和克服滞后性不良影响的能力是该文研究的重点。在分析AQM采用传统PID存在的问题的基础上,提出了一种时滞网络的自适应主动队列管理(FAGPID)算法。由模糊控制器实现PID参数对动态网络环境的在线自适应调整;成功引入灰预测算法实现反馈数据的超前预测,补偿滞后。仿真对比AQM环境中FAGPID,传统PID以及基于模糊免疫PID(FIGPID)的算法,可知FAGPID相对于FIGPID复杂度低,但FAGPID与FIGPID性能相当,均能克服滞后的影响,能快速稳定地适应动态网络环境,收敛于期望队列长度,具有较小的丢包率,优于传统PID算法。     

EMA-PRBDS: efficient multi-attribute packet rank based data scheduling in wireless sensor networks for real-time monitoring systems

ABSTRACT

In recent years, Wireless Sensor Networks (WSNs) are widely placed in real-time monitoring systems like environmental, structural, patient monitoring, etc. The major criterion for WSN includes energy efficiency and network lifetime. Scheduling is used as a large number of data packets focus on the same queue at the same time. Only limited data scheduling schemes have been implemented in WSN to enhance the performance. The existing First Come First Serve (FCFS) and Dynamic Multilevel Priority (DMP) have some technical challenges like delay, packet drop and high energy consumption due to starvation and deadlock. In this paper, we proposed a new algorithm to optimise and rank the incoming data packets based on multi-attributes decision-making methodology named as Packet Rank Based Data Scheduling (PRBDS), the algorithm selects packet priority, deadline, and size as the metrics to rank the incoming data packets. A simulation result shows when compared with existing scheduling, PRBDS not only provides less energy consumption, also significantly reduces the packet drop and increases the lifetime. Thus, the proposed algorithm is most suitable for real-time monitoring system since it combines data ranking method with scheduling algorithm to create accurate and reliable results to evaluate the incoming data packets.     

Designing a binary controller to enhance end-to-end congestion control

Active queue management (AQM) is proposed to enhance end-to-end congestion control through purposefully dropping packets in the intermediate nodes. In this letter, a novel packet dropping mechanism is developed through designing a binary controller applying the robust control theory. The new mechanism can simplify the manipulation on the AQM router so as to be helpful for implementing the high performance router. The numerical simulation results show that the binary controller can satisfy with the technical requirements for AQM