基于分形点过程自相似流的队列性能分析

通过对交换机排队系统进行仿真,分析了以分形点过程( FPP )自相似业务流为输入的排队系统的性能.仿真结果显示,自相似业务流量模型下队列的性能与传统指数流量模型下的队列性能大不相同.文中所获得的仿真结果可用于网络流量模型、网络设计、网络拥塞控制和流量工程等.     

网络流量的联合多重分形模型及特性分析

网络尺度行为的发现提供了用数学模型方法研究网络流量特性的可能性.本文基于连乘瀑布过程与K分布过程提出了联合多重分形(JMF)网络流量模型,该模型以尺度函数与矩因子的联合作为主要特征函数来研究网络流量的特性.理论分析及由实测网络流量数据的仿真结果表明,JMF模型可以较客观地同时描述网络流量短期分形行为与长期自相似行为,且实现复杂度小.其中尺度函数能够刻画时间尺度对流量特性的影响,矩因子描述了同一时间尺度上流量突发性的变化,二者的联合较好地描述了网络流量的短期行为,而模型的统计特性则刻画了流量的长期行为特征.     

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.     

基于离散小波变换的网络流量多重分形模型

网络流量过程中所蕴含的分形尺度特性对网络性能有显著的影响。因此研究能全面准确地刻画网络流量过程在小时间／空间尺度上的复杂奇异性特征和大时间／空间尺度上的长程依赖性特征的流量模型对Internet网络工程有重要的意义。本文对实测的流量数据(从著名的校园网和国内著名的ISP)进行了分析，利用小波技术构建了一个新的网络流量的多重分形模型，通过模拟验证，发现该新模型能以较简洁的形式捕捉实际网络流量特性，并具有刻画真实流量数据中的多重分形特征的能力。     

引入调节因子和小波方法的多重分形模型

针对目前广域网流量多重分形模型不能准确拟合真实网络流量,文中基于瀑布过程建立了一个网络流量多重分形模型,该模型用Burst指数分布来调节乘数因子,用Haar小波方法产生的序列来拟合随机变量.并通过真实网络流量来检验该模型,检验结果:引入了调节因子和小波序列的模型能够比其他分布更准确地拟合广域网流量.     

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.     

基于非平稳型流量队列模型的Internet流量测量研究

针对大规模细粒度网络流量测量的现实困难,本文引入一种非平稳型流量队列模型NTT,直接对粗粒度的流量采样进行建模.NTT模型是大量活跃的流量队列的迭加,每个队列内部的流量变化过程用分形高斯噪声过程FGN描述,队列的到达过程形成非同构的泊松过程,队列的生存周期服从指数分布.对CERNET主干网的实际流量测量分析验证了NTT模型的有效性,证实了NTT模型可用于基于各种粒度的流量测量的网络行为研究.     

一种改进的光纤通道存储扩展流量控制方法

 存储扩展是容灾的基础,为克服光纤通道与扩展网络流量控制不同步对存储扩展性能的影响,提出了一种改进的光纤通道存储扩展流量控制方法,根据扩展网关中缓存队列长度与设定的队列高、低门限值间的关系调整Credit更新频率.建立了基于OPNET的仿真模型,仿真结果表明:改进的流量控制方法能降低数据的排队时延,提高存储扩展的性能.     

网络流量模型的非线性特征量的提取及分析

本文基于相空间重构理论,在高维相空间中对网络流量的宏观和微观特性进行研究分析.首先,提取网络流量的宏观非线性特征量,如关联维数、Kolmogorov熵和最大Lyapunov指数,实现了网络流量时序非线性动力学特性的定量分析.然后,通过对四种典型突发性流量模型的多重分形谱的计算,揭示了流量模型不同层次的行为特征,并给出了刻画突发性流量的有效微观参数.为进一步利用混沌动力学理论对网络行为的控制和建模奠定了基础.     

结合多重分形的网络流量非线性预测

通过分析树型多重分形结构的相关性发现，多重分形可以把非平稳且具有长相关（LRD）和分形特性的网络流量序列转化为可用短相关（SRD）模型表示的序列组。利用多重分形这种将时间序列分解为多层的能力，提出了一种结合多重分形的FIR神经网络流量预测模型（MF-FIR，multifractal FIR network）。MF-FIR合理地利用了流量序列的LRD信息，具有很好的多步预测性能，可以满足通信系统在线预测的要求。     

Distributed and Energy-Aware MAC for Differentiated Services Wireless Packet Networks: A General Queuing Analytical Framework

We present a novel queuing analytical framework for the performance evaluation of a distributed and energy-aware medium access control (MAC) protocol for wireless packet data networks with service differentiation. Specifically, we consider a node (both buffer-limited and energy-limited) in the network with two different types of traffic, namely, high-priority and low-priority traffic, and model the node as a MAP (Markovian arrival process)/PH (phase-type)/1/K nonpreemptive priority queue. The MAC layer in the node is modeled as a server and a vacation queuing model is used to model the sleep and wakeup mechanism of the server. We study standard exhaustive and number-limited exhaustive vacation models both in multiple vacation case. A setup time for the head-of-line packet in the queue is considered, which abstracts the contention and the back-off mechanism of the MAC protocol in the node. A nonideal wireless channel model is also considered, which enables us to investigate the effects of packet transmission errors on the performance behavior of the system. After obtaining the stationary distribution of the system using the matrix-geometric method, we study the performance indices, such as packet dropping probability, access delay, and queue length distribution, for high-priority packets as well as the energy saving factor at the node. Taking into account the bursty traffic arrival (modeled as MAP) and, therefore, the nonsaturation case for the queuing analysis of the MAC protocol, using phase-type distribution for both the service and the vacation processes, and combining the priority queuing model with the vacation queuing model make the analysis very general and comprehensive. Typical numerical results obtained from the analytical model are presented and validated by extensive simulations. Also, we show how the optimal MAC parameters can be obtained by using numerical optimization     

An adaptive AQM to provide delay guarantees for differentiated services

RIO（RED with IN and OUT） is the primary queue management mechanism proposed for assured forwarding in the DiffServ （Differentiated Service） framework. Although RIO can generally provide bandwidth guarantees, its queuing delay is sensitive to the traffic load. This paper presents a qualitative explanation for its origin. As a solution, an Adaptive RIO for Delay （ARIO-D） is proposed to provide guaranteed delay for multimedia traffic. Simulation results show that by trading loss for delay, ARIO-D can effectively improve the robustness of RIO under different and dynamic traffic, and provide stable and differentiated performance of queuing delay without any degradation in performance of throughput.     

The analysis of a queue arising in overflow models

A methodology is presented for analyzing a queuing submodel which frequently arises in the study of overflow models. In this submodel a finite capacity, multiserver queue with exponentially distributed service times, and arriving traffic consisting of a Poisson parcel and several overflow parcels, are assumed. By modeling the overflow parcels as interrupted Poisson processes, an exact queuing analysis is possible. The analysis yields the steady-state queue length distribution, and for each input parcel: (1) the steady-state queue length distribution at arrivals; (2) the probability that an arriving call is blocked (parcel blocking); and (3) the waiting time distribution of an arriving call, in addition to a complete characterization of the overflow due to each parcel     

Switched bath Bernoulli process (SBBP) and the discrete-timeSBBP/G/1 queue with application to statistical multiplexer performance

A doubly stochastic point process is proposed and analyzed. It is a switched batch Bernoulli process (SBBP) for modeling bursty and correlated input to discrete-time queuing systems. Through the investigation of the counting process, statistical characterization measures of the SBBP are explicitly obtained. A discrete-time single-server queue with SBBP input and general service time (SBBP/G/1) is then considered. The SBBP/G/1 queue has a potential applicability to a statistical multiplexer in the network. The supplementary variable technique is used to obtain the probability generating functions of performance measures in the SBBP/G/1 queue. It is shown how the SBBP is suitable for analyzing a discrete-time queue with bursty and correlated input     

基于CTMC和状态空间模型的宽带无线接入网的QoS性能研究

为了实现同一地域范围内的众多用户在有限带宽条件下提出的高QoS要求,本文对基于IEEE 802.16标准的宽带无线接入网中数据包级QoS（Quality of Service）性能进行了研究.具体做法是,首先采用批马尔可夫到达过程（BMAP,Batch Markov Arrival Process）和连续时间马尔科夫链（CTMC,Continuous Time Markov Chain）对到达过程和流量源进行建模,得到更符合实际和更准确的排队模型;然后基于状态空间,对一个无线接入网络系统进行建模,通过对得到的系统模型并结合前面得到的排队模型的深入分析,从而获得该模型下的各项QoS性能指标,如平均队列长度、丢包率、队列吞吐量和平均包时延.仿真实验结果表明,本文提出的算法模型相比于其他典型的算法模型,能够使得各项QoS性能指标有较大的改善和提高.     

Multiscale Queueing Analysis

This paper introduces a new multiscale framework for estimating the tail probability of a queue fed by an arbitrary traffic process. Using traffic statistics at a small number of time scales, our analysis extends the theoretical concept of the critical time scale and provides practical approximations for the tail queue probability. These approximations are non-asymptotic; that is, they apply to any finite queue threshold. While our approach applies to any traffic process, it is particularly apt for long-range-dependent (LRD) traffic. For LRD fractional Brownian motion, we prove that a sparse exponential spacing of time scales yields optimal performance. Simulations with LRD traffic models and real Internet traces demonstrate the accuracy of the approach. Finally, simulations reveal that the marginals of traffic at multiple time scales have a strong influence on queueing that is not captured well by its global second-order correlation in non-Gaussian scenarios.     

Performance of a nonblocking space-division packet switch in a timevariant nonuniform traffic environment

The authors study the performance of a nonblocking space-division packet switch, given that the traffic intensities at the switch not only are nonuniform but also change as a function of time. A finite-state Markov chain is used as an underlying process to govern the time variation of traffic for the entire switch. The packet arrivals at each input form an independent Bernoulli process modulated by the underlying Markov chain. The output address of each packet is independently and randomly assigned with probability distributions, which are also modulated by the Markov chain. Provided that the traffic on each output is not dominated by individual inputs the service time of each output queue for sufficiently large switches can be characterized by an independent Markov modulated phase-type process. A matrix geometric solution for the resultant quasi-birth-death type queuing process is presented. The maximum throughput is obtained at the system saturation. The performance of the switch is numerically examined under various traffic conditions. A contention priority scheme to improve the switch performance is proposed     

Performance Analysis of Network Coding Based Two-Way Relay Wireless Networks Deploying IEEE 802.11

In this paper, we investigate the performance analysis of the IEEE 802.11 DCF protocol at the data link layer. We analyze the impact of network coding in saturated and non-saturated traffic conditions. The cross-layer analytical framework is presented in analyzing the performance of the encode-and-forward (EF) relaying wireless networks. This situation is employed at the physical layer under the conditions of non-saturated traffic and finite-length queue at the data link layer. First, a model of a two-hop EF relaying wireless channel is proposed as an equivalent extend multi-dimensional Markovian state transition model in queuing analysis. Then, the performance in terms of queuing delay, throughput and packet loss rate are derived. We provide closed-form expressions for the delay and throughput of two-hop unbalanced bidirectional traffic cases both with and without network coding. We consider the buffers on nodes are unsaturated. The analytical results are mainly derived by solving queuing systems for the buffer behavior at the relay node. To overcome the hidden node problem in multi hop wireless networks, we develop a useful mathematical model. Both models have been evaluated through simulations and simulation results show good agreement with the analytical results.     

基于FBM模型的自相似网络排队性能分析

利用能够反映自相似特性的FBM模型,采用G/D/1排队模型研究了自相似性对网络性能的影响,讨论了在Norros给出的缓冲区溢出概率公式的基础下,FBM模型为输入时,网络平均排队延迟的解析公式.对理论分形流量和实际测量流量进行了仿真实验,验证了结果的正确性和有效性.