Ad-hoc网络PSD拥塞控制算法

神经元PID算法能较好地控制队列长度,但其神经元增益对被控对象的状态较为敏感,基于试凑和经验的设定往往使控制效果难以保证。基于TCP拥塞窗口加法增大、乘法减小原则和排队机制,推导出拥塞窗口与丢弃概率、队列长度的微分方程,再对方程进行线性化,获得Ad-hoc网络TCP/AQM控制系统模型。基于该模型,将递推计算修正功能引入神经元PID,设计了一种神经元自适应PSD的AQM。该算法可以在线调整神经元增益。NS仿真表明,在无线分组丢失、突发流及链路容量变化的Ad-hoc网络中,PSD队列管理性能优于神经元PID。     

基于混合流拥塞控制的Ad Hoc网络视频传输

基于TCP反馈的主动队列管理算法会无差别地丢弃UDP分组,导致视频质量下降.根据TCP/UDP发送特性和混合流排队机制,推导拥塞窗口、丢弃概率及混合流队列长度的微分方程,通过线性化获得Ad Hoc网络混合流AQM(active queue management)控制模型,提出了一种减少UDP丢弃率的PI-V主动队列管理算法.当视频画质下降时,算法依据视频帧权重与分组长度,动态地调整UDP视频流的丢弃概率.NS(network simulator)仿真表明,PI-V算法优于PI与去尾算法,提高了视频传输质量0.82 d B~2.22 d B的峰值信噪比(PSNR).     

网络拥塞控制模型Hopf分岔的PD控制

网络拥塞会导致信息丢失,时延增加,甚至系统崩溃。由于无线接入网络中的时变衰落和分组错误率,使得TCP协议在网络拥塞控制更加复杂。TCP Westwood是专门为高速无线网络设计的,大大提高了网络带宽的利用率,改善了网络性能。TCP Westwood/AQM拥塞控制的连续流体流模型被引用,源端采用TCP Westwood拥塞控制协议,路由器端采用主动队列管理(AQM)机制中的随机早期检测(RED)算法。为了延迟无线接入网络拥塞控制模型中霍普夫(Hopf)分岔现象的发生,采用比例微分(PD)控制器,通过选择通信延迟作为分岔参数,分析无线网络系统中的Hopf分岔行为,并由理论分析得知当分岔参数超过临界值时系统发生Hopf分岔。利用中心流形和规范型理论,推导得出系统发生Hopf分岔的条件和反映Hopf分岔性质,方向和周期的参数,数值仿真验证理论分析的准确性,表明PD控制器的有效性。     

基于微分先行PI的主动队列管理算法

主动队列管理(AQM)作为一种重要的IP层拥塞控制策略，对于提高Internet的服务质量起到了关键性的作用。简要介绍了AQM算法的研究现状和AQM中的PI算法，依据TCP拥塞控制策略基于数据包丢弃的窗口变化机制，设计了一种基于微分先行PI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采用一定的微分校正原则，实时调整进入该路由器数据包的丢弃概率，使路由器中的队列长度能够稳定在参考值附近。仿真结果表明，该算法与PI算法相比具有更小的超调量，可以明显的加快收敛的速度，从而使Internet的服务质量有更大程度的提高。     

Ad Hoc中的TCP改进方案——Adaptive ADTCP

在分析无线自组网特点及其对TCP性能影响的基础上,提出了一种能够自适应无线自组网状态的TCP改进方案(Adaptive ADTCP）。Adaptive ADTCP在明确辨识网络状态的前提下,首先根据前向路径跳数自适应地调整拥塞窗口增长因子,限制源节点TCP拥塞窗口过分增长,避免造成网络拥塞;同时源节点TCP根据当前拥塞窗口自适应改变发送的分组长度,充分利用网络资源。仿真实验表明,在网络重负载和节点高速移动情况下,Adaptive ADTCP对数据传输的吞吐量有较大提升。     

基于限速的Ad hoc网络混合流拥塞控制研究

主动队列管理(AQM)的基础是TCP反馈机制,所以AQM在处理UDP与TCP混合流时无法控制UDP流量,导致非视频流影响视频UDP的传输质量。根据TCP拥塞窗口特性和混合流排队机制,推导了Ad hoc网络TCP/UDP的AQM模型,据此提出了一种基于UDP限速的PI主动队列管理算法。限速算法根据实际流速与设定流速之差,标记非视频UDP分组优先级并按从低到高的顺序丢弃分组。NS仿真表明,与PI控制相比,新算法实现了非视频UDP的流量控制,提高了视频传输质量0.98dB的峰值信噪比。     

一种新的主动队列管理算法

提出一种新的主动队列管理（AQM）算法。本算法以V. Misra的TCP流量随机微分方程模型为基础,在计入窗口限制的约束条件下,由局部线性化方法导出本文主动队列管理模型的传递函数,并以其作为受控对象,利用比例积分微分（PID）调节器控制该传递函数输出与理想队列长度之差。仿真分析表明,本算法性能优于RED和ARED算法。     

无线自组网TCP吞吐量上界研究

对进入无线自组网节点的TCP数据流进行漏桶管制,节点为TCP提供基于速率-延迟模型的服务保障,在已有无线自组网链路吞吐量模型的基础上利用网络演算理论推导TCP数据流的吞吐量上界模型。在网格拓扑的无线自组网环境下,TCP数据流的仿真结果都在数值计算的上界范围内,从而表明基于网络演算的无线自组网TCP吞吐量性能上界模型具有较好的性能,同时也表明现有TCP协议在无线环境下还存在较大的改进空间。     

基于网络演算的无线自组网TCP丢包率上界研究

精确的TCP丢包率上界对无线环境下TCP协议的性能改进具有指导意义;对进入无线自组网节点的TCP数据流进行漏桶管制,节点为TCP流提供基于速率-延迟(Rate-Latency)模型的服务保障,在已有无线自组网链路吞吐量模型的基础上利用网络演算理论推导了TCP数据流的丢包率上界模型;在网格拓扑的无线自组网环境下,TCP数据流丢包率的仿真结果都在数值计算的上界范围之内,表明基于网络演算的无线自组网TCP丢包率性能上界模型具有较好的性能.     

主动队列管理中P I 字节模式和包模式

主动队列管理(AQM)是近年来TCP端到端拥塞控制的一个研究热点，其中PI拥塞控制机制是建立在RED拥塞控制基础上的一种控制机制．PI机制基于两种方法控制网络拥塞现象：跟踪实时队列长度及拥塞情况下以一定概率丢弃到达队列的数据包．以上方法的计算可以基于包数目或字节数，而方法选择的不同对网络会产生不同的影响．仿真量化性地测定使用不同队列计算和标注方法情况下对通信性能产生的影响．同时，PI控制器与RED控制器在相同模式和参数设置下进行比较，可显示出PI控制具有一定的优越性．     

应用于Ad Hoc网络TCP/AQM的神经网络PID控制器优化设计

主动队列管理(AQM)PID(Proportional integral derivative)算法的控制效果取决于比例、积分及微分系数的整定,但传统整定往往基于试凑方法和经验知识。根据Ad Hoc网络参量时变的特点,推导Ad Hoc网络的TCP/AQM模型,利用遗传算法动态调整RBF(Radial Basis Function)神经网络PID控制器系数,提出基于遗传算法的RBF神经网络PID-AQM。仿真表明,相较RBF-PID,新算法在信道状态复杂的Ad Hoc网络健壮性更好,并具有较好的队列控制效果。     

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.     

A robust fractional-order PID controller design based on active queue management for TCP network

In this paper, a robust fractional-order controller is designed to control the congestion in transmission control protocol (TCP) networks with time-varying parameters. Fractional controllers can increase the stability and robustness. Regardless of advantages of fractional controllers, they are still not common in congestion control in TCP networks. The network parameters are time-varying, so the robust stability is important in congestion controller design. Therefore, we focused on the robust controller design. The fractional PID controller is developed based on active queue management (AQM). D-partition technique is used. The most important property of designed controller is the robustness to the time-varying parameters of the TCP network. The vertex quasi-polynomials of the closed-loop characteristic equation are obtained, and the stability boundaries are calculated for each vertex quasi-polynomial. The intersection of all stability regions is insensitive to network parameter variations, and results in robust stability of TCP/AQM system. NS-2 simulations show that the proposed algorithm provides a stable queue length. Moreover, simulations show smaller oscillations of the queue length and less packet drop probability for FPID compared to PI and PID controllers. We can conclude from NS-2 simulations that the average packet loss probability variations are negligible when the network parameters change.     

Active queue management via event-driven feedback control

Active queue management (AQM) is investigated to avoid incipient congestion in gateways to complement congestion control run by the transport layer protocol such as the TCP. Most existing work on AQM can be categorized as (1) ad-hoc event-driven control and (2) time-driven feedback control approaches based on control theory. Ad hoc event-driven approaches for congestion control, such as RED (random early detection), lack a mathematical model. Thus, it is hard to analyze their dynamics and tune the parameters. Time-driven control theoretic approaches based on solid mathematical models have drawbacks too. As they sample the queue length and run AQM algorithm at every fixed time interval, they may not be adaptive enough to an abrupt load surge. Further, they can be executed unnecessarily often under light loads due to the time-driven nature. To seamlessly integrate the advantages of both event-driven and control-theoretic time-driven approaches, we present an event-driven feedback control approach based on formal control theory. As our approach is based on a mathematical model, its performance is more analyzable and predictable than ad hoc event-driven approaches are. Also, it is more reactive to dynamic load changes due to its event-driven nature. Our simulation results show that our event-driven controller effectively maintains the queue length around the specified set-point. It achieves shorter E2E (end-to-end) delays and smaller E2E delay fluctuations than several existing AQM approaches, which are ad hoc event-driven and based on time-driven control theory, while achieving almost the same E2E delays and E2E delay fluctuations as the two other advanced control theoretic AQM approaches. Further, our AQM algorithm is invoked much less frequently than the tested baselines.     

一种改进的主动队列管理算法

传统的主动队列管理算法（AQM：Active Queue Management）存在响应时间较长等问题,PID（Proportional Integral Differentia1） 主动队列管理算法对此作出了一定改进,然而在时延较大时也不能使队列长度收敛到期望值.本文利用BP神经网络自适应控制的特点,针对无线信道（TCP Westwood）提出了一种基于BP神经网络整定的PID主动队列管理算法.     

基于DupAck的Ad Hoc网络TCP性能改进

为改进传输控制协议(TCP)在无线网络环境下的性能,分析Ad Hoc网络数据丢失的原因,提出一种区分无线丢包和拥塞丢包的算法。该算法通过在发送端检测返回的重复Ack的相对单向传输时延,探测到网络真实的拥塞状况,以便采取合理的拥塞控制措施。仿真结果表明,该算法能够正确区分无线丢包和拥塞丢包,改善Ad Hoc网络的TCP性能。     

TCP/AQM系统大时间尺度模型

网络传输连接的往返时延(round-trip times,RTT)大小各不相同,因此TCP/AQM系统本质为一多时滞回路耦合系统.由于RTT分布范围远大于控制量调节周期,这给准确评估控制效果带来很大困难.已有基于控制理论的主动队列管理(active queue management,AQM)算法多以流体流模型为基础进行设计,没有充分考虑RTT和采样周期对系统性能的影响.对于TCP/AQM系统,合理的评价方法是对调节过程进行评价,而非仅评价单个采样周期内的控制量是否合适.本文结合数据驱动控制思想和系统自身特征,统一从路由视角对TCP与AQM之间的交互进行抽象,通过时间扩展从更大的时间尺度去评价控制量调节过程,然后基于此模型设计自适应AQM算法–—大时间尺度AQM算法(large time scale AQM,LTSAQM).仿真结果表明,该算法收敛速度快,排队时延抖动小,特别是在长时滞网络环境下,性能明显改善.