基于非线性干扰观测器的主动队列管理

针对主动队列管理系统存在UDP流干扰的拥塞问题,本文基于非线性干扰观测器提出了一种主动队列管理算法。采用非线性干扰观测器对UDP流干扰进行估计,从而减小了主动队列管理系统的干扰。然后利用设计的非线性干扰观测器,使用反步滑模方法设计了一种主动队列管理算法。由于观测误差的界未知,设计了一种自适应律来避免必须事先知道观测误差的界。仿真结果表明,该算法对UDP流干扰具有较强的鲁棒性,能使队列长度较好地稳定在期望的队列长度附近。     

Active queue management algorithm based on data-driven predictive control

Model predictive control (MPC) is a popular strategy for active queue management (AQM) that is able to incorporate physical and user defined constraints. However, the current MPC methods rely on explicit fluid model of TCP behavior with input time delay. In this paper, we propose a novel AQM algorithm based on data-driven predictive control, called Data-AQM. For Internet system with large delay, complex change and bad disturbance, data-driven predictive controller can be obtained directly based on the input–output data alone and does not require any explicit model of the system. According to the input–output data, the future queue length in data buffer, which is the basis of optimizing drop probability, is predicted. Furthermore, considering system constraints, the control requirement is converted to the optimal control objective, then the drop probability is obtained by solving the optimal problem online. Finally, the performances of Data-AQM are evaluated through a series of simulations.     

基于非线性控制方法的AQM算法

首先利用非线性控制方法中的积分反步法设计了一种AQM算法,接着使用非线性控制方法中的模糊滑模变结构控制方法进行AQM算法的设计.仿真结果表明,与积分反步法相比,基于模糊滑模变结构控制的AQM算法性能上优于基于积分反步法的AQM算法.与基于线性控制方法的PID控制方法相比,基于积分反步法的AQM算法性能上优于基于PID控制的AQM算法.     

Active queue management algorithm focusing on fairness and low delay

The popularity of delay sensitive applications and high throughput applications in the Internet made the caches of routers and switches larger,resulting in the high latency and high jitter rate of network traffic.With the growth of mobile applications based on the high bandwidth non-response flows,the network bottleneck resource utilization becomes more unbalanced,and the resources distribution of the whole network was difficult to be guaranteed.In order to alleviate these problems,considering the delay control and suppression of high bandwidth non-response flow,an active queue management algorithm focusing on fairness and low delay named FLDA was proposed based on Sample-Match,L-LRU cache and probabilistic packets dropping.Experimental results show that under the interference with high bandwidth non-responsive flows,FLDA can better maintain the queue stability,the fairness of resource utilization of the bottleneck link and the low delay.     

基于反步滑模控制的TCP网络的主动队列管理

针对TCP网络的拥塞问题,考虑到网络本身存在参数不确定因素和非响应流的干扰,基于反步滑模控制提出了一种主动队列管理算法。在总的不确定的界已知而且不必很小的情况下,设计了一种反步滑模控制器来补偿系统不确定所带来的影响。仿真结果表明,该方法对TCP网络的复杂变化具有较好的鲁棒性和较快的系统响应。     

Active intra-ONU scheduling with proportional guaranteed bandwidth in long-reach EPONs

The unused slot remainder (USR) problem in Ethernet Passive Optical Networks and long-reach Passive Optical Networks (LR-PONs) results in both a lower bandwidth utilization and a greater packet delay. In a previous study by the current group, an Active intra-ONU Scheduling with predictive queue report scheme was proposed for resolving the USR problem by predicting the granted bandwidth in advance based on the arrival traffic estimates of the optical network units (ONUs). However, it was found that the higher bandwidth prediction error in the proposed scheme prevents the network performance from being improved. Accordingly, the present study proposes a non-predictive-based ONU scheduling method designated as Active intra-ONU Scheduling with proportional guaranteed bandwidth (ASPGB) to improve the performance of LR-PONs. In the proposed method, the maximum guaranteed bandwidth of each ONU is adapted dynamically in accordance with the ratio of the ONU traffic load to the overall system load. Importantly, the proposed dynamic bandwidth allocation approach reduces the dependence of the network performance on the granted bandwidth prediction since the maximum guaranteed bandwidth determined by the Optical Line Terminal more closely approaches the actual bandwidth demand of each ONU. To solve the idle time problem arising in the event of an excess bandwidth reallocation, ASPGB is integrated with an improved early allocation (IEA) algorithm (a kind of Just-In-Time scheduling). The simulation results show that the IEA-ASPGB scheme outperforms previously published methods in terms of bandwidth utilization and average packet delay under both balanced and unbalanced traffic load conditions.     

REM: active queue management

We describe a new active queue management scheme, random exponential marking (REM), that aims to achieve both high utilization and negligible loss and delay in a simple and scalable manner. The key idea is to decouple the congestion measure from the performance measure such as loss, queue length, or delay. While the congestion measure indicates excess demand for bandwidth and must track the number of users, the performance measure should be stabilized around their targets independent of the number of users. We explain the design rationale behind REM and present simulation results of its performance in wireline and wireless networks     

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.     

The BLUE active queue management algorithms

In order to stem the increasing packet loss rates caused by an exponential increase in network traffic, the IETF has been considering the deployment of active queue management techniques such as RED (random early detection) (see Floyd, S. and Jacobson, V., IEEE/ACM Trans. Networking, vol.1, p.397-413, 1993). While active queue management can potentially reduce packet loss rates in the Internet, we show that current techniques are ineffective in preventing high loss rates. The inherent problem with these algorithms is that they use queue lengths as the indicator of the severity of congestion. In light of this observation, a fundamentally different active queue management algorithm, called BLUE, is proposed, implemented and evaluated. BLUE uses packet loss and link idle events to manage congestion. Using both simulation and controlled experiments, BLUE is shown to perform significantly better than RED, both in terms of packet loss rates and buffer size requirements in the network. As an extension to BLUE, a novel technique based on Bloom filters (see Bloom, B., Commun. ACM, vol.13, no.7, p.422-6, 1970) is described for enforcing fairness among a large number of flows. In particular, we propose and evaluate stochastic fair BLUE (SFB), a queue management algorithm which can identify and rate-limit nonresponsive flows using a very small amount of state information.     

一种加强的主动队列管理算法--EBLUE

作为一种典型的主动队列管理算法,BLUE明显不同于其它方法,它使用丢包和连接空闲事件来控制拥塞。试验表明BLUE的丢包率明显小于RED,但是其参数设置仍然存在一些不足之处。本文在BLUE算法的基础之上,通过引进自适应的思想对其进行了改进,提出了一种加强的BLUE队列算法——EBLUE。大量的仿真实验表明本文的改进算法能够进一步提高BLUE的性能。     

An adaptive virtual queue (AVQ) algorithm for active queue management

Virtual queue-based marking schemes have been recently proposed for Active Queue Management (AQM) in Internet routers. We consider a particular scheme, which we call the Adaptive Virtual Queue (AVQ), and study its following properties: its stability in the presence of feedback delays, its ability to maintain small queue lengths, and its robustness in the presence of extremely short flows (the so-called web mice). Using a linearized model of the system dynamics, we present a simple rule to design the parameters of the AVQ algorithm. We then compare its performance through simulation with several well-known AQM schemes such as RED, REM, Proportional Integral (PI) controller, and a nonadaptive virtual queue algorithm. With a view toward implementation, we show that AVQ can be implemented as a simple token bucket using only a few lines of code.     

主动队列管理中的PID控制器

作为对终端系统上拥塞控制的一种补充,中间节点上的主动队列管理(AQM)策略在保证较高吞吐量的基础上有效地控制队列长度,从而实现了控制端到端的时延,保证QoS的目的。C.Hollot等人(2001)用经典控制理论中频域校正的方法设计了用于AQM的PI控制器,但参数整定上的试凑方法不免代有盲目性;算法的瞬态性能指标也不够理想。为此,该文引入了微分环节来增强系统的响应能力,同时给出了基于稳定裕度的参数整定方法,使PID控制器的稳定性有了绝对保障。仿真试验表明PID算法的调节时间远远短于PI控制器,从而为在负载瞬息万变的网络环境中实现控制分组排队等待时间的目标提供了有力的技术保障。     

PDAVQ：一种基于PD控制的自适应虚拟队列管理算法

提出了一种新的基于比例差分控制的自适应虚拟队列管理(AVQ)算法—PDAVQ,用于对网络链路中产生的拥塞进行控制,以达到有效利用网络带宽,使整个网络系统达到稳定,缓解网络拥塞的目的。而且本文对所提算法运用控制理论对系统的稳定性进行了证明,给出了满足系统稳定性条件的参数选择方法和 PDAVQ 算法的具体描述。最后,通过 ns2 仿真实验与现有的 AVQ 算法比较,结果表明,所提 PDAVQ 算法具有较高的吞吐率、较低的链路延迟和数据丢失率,并能更快的使整个网络系统达到稳定,具有较好的网络性能。     

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.     

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.     

Adaptive fuzzy sliding mode active queue management algorithms

Active queue management (AQM) is aimed at achieving the tradeoff between link utilization and queuing delay to enhance TCP congestion control and is expected to perform well for a wider-range of network conditions. Static AQM schemes despite their simplicity, often suffer from long response time due to conservative parameter setting to ensure stability. Adaptive parameter settings, which might solve this problem, remain difficult from implementation point of view. In this paper, we propose an adaptive fuzzy sliding mode (AFSM) AQM algorithm to achieve fast response and yet good robustness. The AFSM algorithm uses the queue length and its differential as the input of AQM and adjusts fuzzy rules by the measurement of packet loss ratio dynamically. The stability analysis under heterogeneous round trip times provides guidelines for parameter settings in AFSM and guarantees that the stability of AFSM is independent of the active TCP flows. This merit as well as other performances is examined under various network environments. Compared to some typical AQMs, the AFSM algorithm trades off the throughput with queuing delay better and achieves a higher per-flow throughput. Finally, AFSM can be executed at a scale of seconds with the least fuzzy rules.     

A stochastic approximation approach to active queue management

Recently, a dynamic adaptive queue management with random dropping (AQMRD) scheme has been developed to capture the time-dependent variation of average queue size by incorporating the rate of change of average queue size as a parameter. A major issue with AQMRD is the choice of parameters. In this paper, a novel online stochastic approximation based optimization scheme is proposed to dynamically tune the parameters of AQMRD and which is also applicable for other active queue management (AQM) algorithms. Our optimization scheme significantly improves the throughput, average queue size, and loss-rate in relation to other AQM schemes.     

队列管理算法对VOIP QoS的提高

VoIP日益成为受用户欢迎的IP网络服务,然而,这些IP网络上的VOIP通话质量却并不能得到令人满意的保证,尤其是当网络拥塞的时候。文中提出了一种不涉及改造网络结构,低成本地提高VOIP的通话质量的方法。通过随机早期检测算法的应用,可以有效地降低VOIP通话的延迟、抖动和有效丢包率,从而提高VOIP的通话质量。