基于AOS的Hurst-优先级自适应RED与动态调度算法

为有效传输空间数据系统中多类型、大容量、突发性的数据,基于高级在轨系统(AOS)虚拟信道复用技术,提出了一种自相似参数Hurst-优先级自适应的随机早检测(RED)与动态调度算法——HPRED-DS。该算法在队列管理中设计了基于Hurst参数与优先级的2级丢弃分组策略,在虚拟信道调度中设计了VIP/同步/异步混合的动态调度模式,并将队列管理与虚拟信道调度有效结合起来。实验结果表明该算法在保持高处理效率和吞吐率的基础上,稳定了队列长度,降低了排队延时和延时抖动,并能满足AOS中不同业务的传输要求。     

一种无线网络中基于ARQ的拥塞控制方法

提出了一种适用于无线网络的基于多拒绝自动请求重传（ARQ）算法的拥塞控制方法。谊方法结合随机早探洲（RED）算法，通过ARQ发送窗口和分割队列长度以及重传率进行拥塞控制。仿真表明，这种方法能预测链路拥塞，反馈链路拥塞程度，提高链路吞吐率。     

基于时间槽的自相似流量随机早检测算法——SFRED

分析研究了网络流量的自相似和长相关性,并基于分形布朗运动模型导出了自相似流量环境RED算法分组丢失概率的一种计算方法,从而提出了基于时间槽的自相似流量随机早检测队列管理算法SFRED.该算法在每个时间槽内计算一次分组丢失概率,大大降低系统负担.NS2仿真实验表明SFRED算法性能明显优于RED,能够很好地在自适应流背景下控制队列长度,并具有良好的吞吐量性能.     

一种新的IP分组丢弃策略PRDP

该文分析了IP业务在MPLS/DiffServ上运行的特点,从考虑业务量工程性能的角度出发提出了一种新的IP分组优先级的划分方法,并在此基础上给出了一种新的IP分组丢弃算法基于优先级的丢弃策略(PBDP)。考虑到随机早检测策略(RED)的优点,将PBDP与RED相结合,得到一种改进的算法基于优先级的RED策略(PRDP),仿真结果表明这种算法在提高全网性能上有优势,其性能优于传统的尾丢弃策略。     

基于分形布朗运动的等效带宽及其参数计算算法

在推导一种新型的基于分形布朗运动（fractional brownian motion,FBM）的等效带宽计算模型的基础上,提出了基于小波分析的Hurst参数计算模型。首先给出了ON／OFF数据源的数学定义,然后在此基础上推导了基于FBM的等效带宽计算模型。对模型的敏感性分析表明,Hurst参数是该模型的重要参数,文中提出了一种改进的基于小波分析的Hurst参数检测算法。仿真证明,所提的等效带宽模型正确有效,Hurst参数检测算法精度显著提高。     

RED分组丢弃算法性能研究

 本文研究了在ATM交换机上实现的RED算法的性能.在固定有效带宽、时变有效带宽情况下和同种、异种业务环境下,研究了RED算法的通过率、公平性和时延等性能.经研究表明:RED算法有必要与EPD算法相结合,构成RED+EPD算法.采用RED+EPD算法的ATM交换机通过控制平均排队长度,有效地减小了交换机的平均排队时延.通过与其他分组丢弃算法进行性能比较表明:采用RED+EPD算法的ATM交换机,可提供比EPD算法略高的通过率,更好的公平性和更低的排队时延,能较好地支持具有时延要求的业务.     

一种支持VoIP语音高优先级传输的WLAN系统设计

针对无线局域网（WLAN）多址接入的特点以及VoIP业务自身的质量要求，提出了一种设计方法，将上下行数据发送分离，支持实时业务的上下行对等传输，同时通过一种改进的早期随机检测（RED）算法，实现基于语音抖动参数的流量控制，为语音业务提供QoS保证。     

一种基于负载的公平性主动队列管理算法

针对随机早期检测（RED,Random Early Detection）算法存在的公平性问题,提出了一种基于负载的公平性主动队列管理算法（LFED）。该算法通过引入网络负载和队列这两个概念,有效地判断当前网络拥塞程度,同时使用改进的丢包率公式,并且借鉴CHOKe算法的惩罚机制对非响应流进行有效惩罚,以保证不同数据流之间的公平。仿真实验表明,与RED和CHOKe相比,LFED可以得到稳定的瞬时队列长度和减少分组丢弃率,具有较好的公平性和稳定性。     

串联排队RED、ERED网络分析模型

基于串联排队网络理论,建立了包括多个网络节点的串联排队RED和ERED分析模型。推导了具有指数分布分组丢失函数的RED算法(ERED)。在概率生成函数域,推导了节点的离去过程,并将其拟合为后续节点的到达过程,从而,刻画了多节点级联拥塞控制的通信场景。通过求解串联排队系统,得出串联排队RED、ERED以及DT 3种AQM机制的网络性能指标,分析了AQM参数设置对其性能的影响。针对不同突发度的业务源,给出每个节点和系统端到端性能指标。     

区分服务模型中的一种动态队列管理算法

在对区分服务模型和RED算法进行分析的基础上，提出了一种基于RED算法的动态队列管理算法。实验结果证明，我们提出的算法在不损害高优先级数据流量的情况下，能较好地实时调整各优先级的门限值，减少网络资源的消耗，提高网络资源的利用率。     

基于分形整形器的GPS系统性能确定上界研究

为了精确求解以自相似业务作为输入的网络性能确定边界问题,在GPS(generalized processor sharing)系统入口处利用分形整形器对自相似业务进行调控,提出了基于分形整形器的GPS系统模型,基于确定性网络演算理论推导了使用自相似业务作为输入时该GPS系统的缓存队列长度、延迟、延迟抖动以及有效带宽等性能确定上界模型。数值结果表明,基于分形整形器的GPS系统性能确定上界模型对自相似业务具有较好的性能。     

一种基于预测PI控制器的自相似网络主动队列管理算法

近年研究发现网络中的业务量呈自相似特征,这种自相似特征显著影响网络的流量控制与排队性能,本文在自相似网络流量可预测的基础上,利用线性回归分析理论进行流量预测,并应用控制理论中的预测PI控制器原理设计了动态矩阵PI控制主动队列管理(Dynamic Matrix PI Control-Active Queue Management,简称DMPIC-AQM)算法,以克服队列的剧烈振荡,保持队列稳定在期望的长度.仿真实验结果表明,DMPIC-AQM算法在网络流量剧烈变化和小期望队列长度的情形下,DMPIC-AQM算法明显优于RED与PI算法.     

FQL‐RED: an adaptive scalable schema for active queue management

In a potentially congested network, random early detection (RED) active queue management (AQM) proved effective in improving throughput and average queuing delay. The main disadvantage of RED is its sensitive parameters that are impossible to estimate perfectly and adjust manually because of the dynamic nature of the network. For this reason, RED performs differently during different phases of a scenario and there is no guarantee that it will have optimal performance. Giving adaptability to RED has been the subject of broad research studies ever since RED was proposed. After a substantial study of AQM schemes and presenting a novel categorization for so‐called modern approaches utilizing artificial intelligence tools to improve AQM, this paper proposes an algorithm enhancing RED as an add‐on patch that makes minimal changes to the original RED. Being built on the basis of AQM schemes like ARED and Fuzzy‐RED, this algorithm inherits adaptability and is able to adjust RED inaccurate parameters regarding network traffic status, trying to optimize throughput and average queuing delay in a scenario. This algorithm is a Q‐learning method enhanced with a fuzzy inference system to provide RED with self‐adaptation and improved performance as a result. Given the name of FQL‐RED, this algorithm outperformed RED, ARED, and Fuzzy‐RED, as the OPNET simulations show. Copyright © 2010 John Wiley & Sons, Ltd.     

自相似流量的主动队列管理算法

该文提出了一种替代随机早期检测(RED)的主动队列管理算法:信号能量的小波分解(wavelet-decomposed signal energy, WDSE)算法。WDSE能够有效地对自相似流量进行拥塞检测和管理。采用小波的二阶子段滤波测量输入流量的能量,基于小波的多分辨率分析可以对到达流量的短期和长期波动进行预报,重新调整主动队列管理的丢弃概率。WDSE可以避免先前主动队列管理所难以解决的参数选择问题,如RED等。该文比较了WDSE和RED的动态性能,显示WDSE能够有效改善系统的暂态特性。仿真证明WDSE比RED能更快地响应负载的变化。此外,WDSE在控制瞬时队列长度的稳态值也具有更好的鲁棒性。     

RED gateway congestion control using median queue size estimates

This paper focuses on the queue size estimation problem in random early detection (RED) gateways. Queue size estimation plays a fundamental role in the congestion control dynamics of RED, as it determines gateways' awareness of network congestion, which in turn determines the packet dropping/marking decision. Conventional RED gateways use exponentially weighted moving averages (EWMA) to estimate the queue size. These infinite impulse response (IIR) filters require very small EWMA weights in order to effectively avoid nonlinear instabilities in RED and to filter out bursty increases in the queue size. While small EWMA weights enable gateways to accommodate transient congestion, they also lead to gateways' failure to closely track rapid queue size depletion and thus causes link under utilization. We investigate the use of simple nonlinear queue size estimators. In particular, we study the congestion control dynamics of a network where adaptive weighted median filters are used for queue size estimation by the gateways. Analytical results for the expected queue size in the steady state are derived. Under this new queue size estimation framework, design guidelines for the remaining RED parameters are provided. Simulation results show that the proposed algorithm provides greater network power, better prevention of global synchronization, and a fairer treatment to bursty traffic than the RED algorithm does.     

基于分形漏桶整形器的通用处理器共享系统性能分析

为了分析自相似业务流对通用处理器共享（GPS）系统性能的影响,研究了GPS系统性能与业务流自相似参数等因素之间的关系.通过使用分形漏桶的包络曲线对进入GPS系统的自相似业务流进行整形,推导了利用自相似业务流作为输入的GPS系统的队列长度和时延统计上界.数值结果与分析显示,基于分形漏桶的GPS系统性能模型对自相似业务流具有较好的性能.     

Network queue scheduling algorithm based on self-similar traffic level grading prediction

Self-similarity characteristic of network traffic will lead to the continuous burstness of data in the network.In order to effectively reduce the queue delay and packet loss rate caused by network traffic burst,improve the transmission capacity of different priority services,and guarantee the service quality requirements,a queue scheduling algorithm P-DWRR based on the self-similarity of network traffic was proposed.A dynamic weight allocation method and a service quantum update method based on the self-similar traffic level grading prediction results were designed,and the service order of the queue according was determined to the service priority and queue waiting time,so as to reduce the queuing delay and packet loss rate.The simulation results show that the P-DWRR algorithm can reduce the queueing delay,delay jitter and packet loss rate on the basis of satisfying the different service priority requirements of the network,and its performance is better than that of DWRR and VDWRR.     

Some results on the self-similarity property in communication networks

Due to the strong experimental evidence that packet network traffic is self-similar in nature, it is important to study the problems to see whether the superposition of self-similar processes retains the property of self-similarity, and whether the service of a server changes the self-similarity property of the input traffic. In this letter, we first discuss some definitions and superposition properties of self-similar processes. We obtain some good results about the property of merging self-similar data streams. Then we present a model of a single server with infinite buffer and prove that when the queue length has finite second-order moment, the input process, being strong asymptotically second-order self-similar (sas-s), is equivalent to the output process which also bears the sas-s property.     

Multihop Virtual Topology Design in WDM Optical Networks for Self-Similar Traffic

In this paper, we consider the problem of designing virtual topologies for multihop optical WDM networks when the traffic is self-similar in nature. Studies over the last few years suggest that the network traffic is bursty and can be much better modeled using self similar process instead of Poisson process. We examine buffer sizes of a network and observe that, even with reasonably low buffer overflow probability, the maximum buffer size requirement for self-similar traffic can be very large. Therefore, a self-similar traffic model has an impact on the queuing delay which is usually much higher than that obtained with the Poisson model. We investigate the problem of constructing the virtual topology with these two types of traffic and solve it with two algorithmic approaches: Greedy (Heuristic) algorithm and Evolutionary algorithm. While the greedy algorithm performs a least-cost search on the total delay along paths for routing traffic in a multihop fashion, the evolutionary algorithm uses genetic methods to optimize the average delay in a network. We analyze and compare our proposed algorithms with an existing algorithm via different performance parameters. Interestingly, with both the proposed algorithms the difference in the queuing delays, caused by self-similar and Poisson traffic, results in different multihop virtual topologies.