一种参数自适应的主动队列管理算法-自适应BLUE

BLUE算法是一种典型的主动队列管理(Active Queue Management,AQM)算法,研究表明BLUE算法优于RED算法.BLUE算法使用丢包事件和链路空闲事件控制网络拥塞.但由于BLUE算法在参数设置方面存在不足,尤其是当TCP连接数突然剧烈变动时,容易导致队列溢出或空闲的频繁发生.该文引进参数自适应机制,提出了自适应BLUE算法,并借鉴了RED算法的早期拥塞检测机制.NS仿真实验表明该算法能有效保持队列长度的稳定,减少队列溢出或空闲现象的发生,在提高链路利用率的同时降低丢包率.     

PAQM: an adaptive and proactive queue management for end‐to‐end TCP congestion control

Two functions, the congestion indicator (i.e. how to detect congestion) and the congestion control function (i.e. how to avoid and control congestion), are used at a router to support end‐to‐end congestion control in the Internet. Random early detection (RED) (IEEE/ACM Trans. Networking 1993; 1 (4):397–413) enhanced the two functions by introducing queue length averaging and probabilistic early packet dropping. In particular, RED uses an exponentially weighted moving average (EWMA) queue length not only to detect incipient congestion but also to smooth the bursty incoming traffic and its resulting transient congestion. Following RED, many active queue management (AQM)‐based extensions have been proposed. However, many AQM proposals have shown severe problems with detection and control of the incipient congestion adaptively to the dynamically changing network situations. In this paper, we introduce and analyse a feedback control model of TCP/AQM dynamics. Then, we propose the Pro‐active Queue Management (PAQM) mechanism, which is able to provide proactive congestion avoidance and control using an adaptive congestion indicator and a control function under a wide range of traffic environments. The PAQM stabilizes the queue length around the desired level while giving smooth and low packet loss rates and high network resource utilization. Copyright © 2004 John Wiley & Sons, Ltd.     

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.     

Advances in Active Queue Management (AQM) Based TCP Congestion Control

Current end-to-end Internet congestion control under tail-drop (TD) queue management experiences performance degradations such as multiple packet losses, high queueing delay and low link utilization. In this paper, we review recently proposed active queue management (AQM) algorithms for supporting end-to-end transmission control protocol (TCP) congestion control. We focus recently developed control theoretic design and analysis method for the AQM based TCP congestion control dynamics. In this context, we analyze the problems of existing AQM proposals in which congestion is detected and controlled reactively based on current and/or past congestion. Then we argue that AQM based TCP congestion control should be adaptive to the dynamically changing traffic situation in order to detect, control and avoid the current and the incipient congestion proactively. Finally, we survey two adaptive and proactive AQM algorithms, PID-controller and Pro-Active Queue Management (PAQM), designed using classical proportional-integral–derivative (PID) feedback control to overcome the reactive congestion control dynamics of existing AQM algorithms. A comparative study of these AQM algorithms with existing AQM algorithms is given. A simulation study under a wide range of realistic traffic conditions suggests that PID-controller and PAQM outperform other AQM algorithms such as random early detection (RED) [Floyd and Jacobson, 18] and proportional-integral (PI) controller [Hollot et al., 24].     

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。     

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.     

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.     

数据流的活动队列管理算法:MBLUE

MBLUE(Modified BLUE)是一种面向数据流的活动队列管理算法.它不是使用平均队列长度指示缓冲区拥塞状态,而是使用数据报丢弃的频率和队列空闲程度来管理网络拥塞.探测瓶颈连接早期的拥塞信息,通过数据报的丢弃和标记避免拥塞.它只维护一个先进先出队列,以较少的数据流状态信息,在不同流之间公平的分配网络带宽.能够适应瞬时的猝发流,能合理控制非TCP数据流,又能够保持较短的平均队列长度,从而控制、减轻网络拥塞.通过TCP/IP网络的模拟,证实算法在公平的分配网络带宽和降低数据报的丢失率上具有较好的鲁棒性.     

Relative loss rate differentiation: performance of short‐lived TCP flows

The relative differentiated service model provides assurances for the relative quality ordering between service classes, rather than for the actual service level in each class. In this paper, we describe a relative loss rate differentiation scheme where packet drop probabilities are determined according to an active queue management (AQM) mechanism based on random early detection (RED) in a first‐in first‐out (FIFO) queue, are weighted in inverse proportion to the price that the network operator assigns to each service class. Basically, we describe a scheme where relative loss rate differentiation is incorporated directly into AQM. Most TCP flows today, particularly Web flows, can be characterized as short‐lived flows. Using simulations with short‐lived TCP flows, we show that the scheme is very effective in ensuring relative loss rate differentiation between service classes during times of network congestion. Copyright © 2004 John Wiley & Sons, Ltd.     

DRED‐MP: Queue management with multiple levels of drop precedence

There is current interest in differentiated service architectures where packets with different priorities can share the same queue. In the case of congestion, packets marked with higher drop probability are preferentially dropped in order to make buffer room for packets marked with lower drop probability. Active queue management (AQM) based on randomized packet dropping has become a key component of this packet forwarding model. This paper extends our previously developed AQM algorithm called DRED with multiple packet drop precedence to allow for priority treatment of traffic in a network. The main advantage of using the DRED algorithm is the lower parameter configuration complexity it offers and the ease of configuration for a wide range of network conditions. Copyright © 2004 John Wiley & Sons, Ltd.     

主动队列管理机制在无线系统中的优化

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。     

Advances in internet congestion control

In this survey, we first review the concept of congestion control with a focus on the Transmission Control Protocol⁄Internet Protocol (TCP⁄IP). We describe many recently proposed algorithms to combat congestion and improve performance, particularly active queue management (AQM) algorithms such as random early detection (RED) and its variants. We then survey control-theoretic analysis and design of TCP congestion control with an AQM scheme. In addition, we discuss three problems associated with AQM proposals: parameter setting, the insensitivity to the input traffic load variation, and the mismatch between macroscopic and microscopic behavior of queue length dynamics. As alternatives to AQM algorithms, we also survey architectural approaches such as modification of source or network algorithms, and economic approaches including pricing or optimization of allocated resources. Finally, we list many open issues that persist in the design, operation, and control of the Internet.     

Simulation comparison of active queue management algorithms in TCP/IP networks

Active Queue Management techniques are recommended to overcome the performance limitations of TCP congestion control mechanisms over drop-tail networks. The main objective of this paper is to present the comparative analysis of the performance of 10 different queue management policies using the OMNeT++ simulator. The AQMs have many parameters which influence their behavior, so some results concerning the parameters selection are given. The algorithms are tested in terms of average queue size, packet delay and packet loss rate in presence of TCP traffic.     

One More Bit is Enough

Achieving efficient and fair bandwidth allocation while minimizing packet loss and bottleneck queue in high bandwidth-delay product networks has long been a daunting challenge. Existing end-to-end congestion control (e.g., TCP) and traditional congestion notification schemes (e.g., ${hbox {TCP+AQM/ECN}}$) have significant limitations in achieving this goal. While the XCP protocol addresses this challenge, it requires multiple bits to encode the congestion-related information exchanged between routers and end-hosts. Unfortunately, there is no space in the IP header for these bits, and solving this problem involves a non-trivial and time-consuming standardization process.      

Random early detection gateways for congestion avoidance

The authors present random early detection (RED) gateways for congestion avoidance in packet-switched networks. The gateway detects incipient congestion by computing the average queue size. The gateway could notify connections of congestion either by dropping packets arriving at the gateway or by setting a bit in packet headers. When the average queue size exceeds a present threshold, the gateway drops or marks each arriving packet with a certain probability, where the exact probability is a function of the average queue size. RED gateways keep the average queue size low while allowing occasional bursts of packets in the queue. During congestion, the probability that the gateway notifies a particular connection to reduce its window is roughly proportional to that connection's share of the bandwidth through the gateway. RED gateways are designed to accompany a transport-layer congestion control protocol such as TCP. The RED gateway has no bias against bursty traffic and avoids the global synchronization of many connections decreasing their window at the same time. Simulations of a TCP/IP network are used to illustrate the performance of RED gateways     

Optimized Congestion Management Protocol for Healthcare Wireless Sensor Networks

The application of Wireless Sensor Networks (WSNs) in healthcare is dominant and fast growing. In healthcare WSN applications (HWSNs) such as medical emergencies, the network may encounter an unpredictable load which leads to congestion. Congestion problem which is common in any data network including WSN, leads to packet loss, increasing end-to-end delay and excessive energy consumption due to retransmission. In modern wireless biomedical sensor networks, increasing these two parameters for the packets that carry EKG signals may even result in the death of the patient. Furthermore, when congestion occurs, because of the packet loss, packet retransmission increases accordingly. The retransmission directly affects the lifetime of the nodes. In this paper, an Optimized Congestion management protocol is proposed for HWSNs when the patients are stationary. This protocol consists of two stages. In the first stage, a novel Active Queue Management (AQM) scheme is proposed to avoid congestion and provide quality of service (QoS). This scheme uses separate virtual queues on a single physical queue to store the input packets from each child node based on importance and priority of the source’s traffic. If the incoming packet is accepted, in the second stage, three mechanisms are used to control congestion. The proposed protocol detects congestion by a three-state machine and virtual queue status; it adjusts the child’s sending rate by an optimization function. We compare our proposed protocol with CCF, PCCP and backpressure algorithms using the OPNET simulator. Simulation results show that the proposed protocol is more efficient than CCF, PCCP and backpressure algorithms in terms of packet loss, energy efficiency, end-to-end delay and fairness.     

A cognitive accountability mechanism for penalizing misbehaving ECN‐based TCP stacks

The introduction of high‐bandwidth demanding services such as multimedia services has resulted in important changes on how services in the Internet are accessed and what quality‐of‐experience requirements (i.e. limited amount of packet loss, fairness between connections) are expected to ensure a smooth service delivery. In the current congestion control mechanisms, misbehaving Transmission Control Protocol (TCP) stacks can easily achieve an unfair advantage over the other connections by not responding to Explicit Congestion Notification (ECN) warnings, sent by the active queue management (AQM) system when congestion in the network is imminent. In this article, we present an accountability mechanism that holds connections accountable for their actions through the detection and penalization of misbehaving TCP stacks with the goal of restoring the fairness in the network. The mechanism is specifically targeted at deployment in multimedia access networks as these environments are most prone to fairness issues due to misbehaving TCP stacks (i.e. long‐lived connections and a moderate connection pool size). We argue that a cognitive approach is best suited to cope with the dynamicity of the environment and therefore present a cognitive detection algorithm that combines machine learning algorithms to classify connections into well‐behaving and misbehaving profiles. This is in turn used by a differentiated AQM mechanism that provides a different treatment for the well‐behaving and misbehaving profiles. The performance of the cognitive accountability mechanism has been characterized both in terms of the accuracy of the cognitive detection algorithm and the overall impact of the mechanism on network fairness. Copyright © 2012 John Wiley & Sons, Ltd.     

PRED:一种具有优先级自适应的队列管理新算法

现有的拥塞控制采用以TCP为核心的基于窗口技术的端到端控制,具有丢包、响应速度慢等缺陷.本文提出的基于优先级的队列管理算法(PRED),使路由器更加精确地管理队列,算法的主要参数能够适应网络负载的动态变化,有效地克服了现有拥塞控制的缺陷.实验结果表明,在相同的配置下,采用PRED的网络在降低丢包率、减少队列抖动等性能上均优于端到端拥塞控制.     

基于速率的主动队列管理算法的性能分析

主动队列管理是解决网络拥塞的主要措施。针对基于队列的主动队列管理算法的不足,提出了一种基于速率的新算法RAQM,该算法以数据到达速率与路由器最大服务速率的差值为指标计算丢包概率,能够快速地对网络流量的变化做出反应,该算法计算简单,而且只需要设置一个参数K。通过现代控制理论分析了RAQM/TCP系统的稳定性。仿真结果表明,RAQM能够维持较低的队列长度并保持队列的稳定,从而减小了分组端到端时延和时延抖动。最后讨论了参数K对算法性能的影响。     

A method for estimating the proportion of nonresponsive traffic at a router

In this paper, a scheme for estimating the proportion of the incoming traffic that is not responsive to congestion at a router is presented. The idea of the proposed scheme is that if the observed queue length and packet drop probability do not match the predictions from a model of responsive (TCP) traffic, then the error must come from nonresponsive traffic; it can then be used for estimating the proportion of nonresponsive traffic. The proposed scheme is based on the queue length history, packet drop history, and expected TCP and queue dynamics. The effectiveness of the proposed scheme over a wide range of traffic scenarios is corroborated using ns-2-based simulations. Potential applications of the proposed algorithms in traffic engineering and control are discussed.