一种自负载降速率包列可用带宽测量算法

基于自负载周期流技术,提出一种采用降速率包列的可用带宽测量方法SLDRT(self-loading decreasing rate train),并全面分析了该算法在多跳网络、突发性背景流的环境下的性能.SLDRT采用单条包列即可实现对可用带宽的高速测量,具备单次采样、准确测量的特性,可通过调整递减因子等参数,提高测量精度,降低测量负载.理论分析和不同背景流场景下的实验结果表明:在多跳、突发性背景流下,SLDRT具有较强的健壮性;与pathChirp,Pathload算法相比,不仅测量精度优良,而且大量缩短了测量时间,减轻了因测量而引入的额外负载.     

基于非液体流模型的可用带宽测量精度

现有的可用带宽测量技术大多基于单跳链路和液体流模型,在突发背景流及多跳链路下测量精度较低。因此,分析了更符合网络实际的非液体流模型,提出了一种参数设置方法,减小了探测包长、探测速率、背景流速率及背景流包长等因素对测量精度的影响。在此基础上,改进了探测包对结构,该结构结合生存时间(TTL)值设置减小了探测包对间隔的测量误差,增强了带宽测量算法在多跳链路环境下的健壮性。仿真表明,基于非液体流模型的参数设置方法及改进的包对结构提高了可用带宽测量精度。     

一种速率自调节可用带宽测量算法

可用带宽是网络路由、网络服务质量、流量工程等方面的一个关键参数。目前很多研究方法都基于PGM模型和PRM模型,但这两种方法大都假设背景流量速率为固定比特流,不适用于低带宽的测试。提出一种端值自调节可用带宽测量算法,该算法充分考虑了低链路带宽的情况。通过对排队延时的处理、探测分组列速率端值自适应调节,实现了端到端可用带宽快速准确的测量。实验结果表明,该算法具有良好的测量效果,尤其在低带宽条件下较其它同类算法提高了测量准确性,加快了测量速度并减小了对网络的影响。     

一种改进离群区间计算的PRM带宽测量算法

主动式网络路径可用带宽测量是目前网络路径带宽测量使用的主要方法,与被动式网络路径可用带宽测量相比,具有更高的灵活性且部署方便。为解决主动式网络路径可用带宽测量定义不明确、通用性不强、协议不规范和结果不准确等问题,规范定义了探测通信协议和报文结构,建立了较为完整、统一和规范的主动式网络路径可用带宽测量框架,提出了序列时延增加度和基于序列时延增加度的离群区间计算方法,改进了网络背景流量分析方法,降低了背景流量对网络路径可用带宽测量的干扰,最后使用NS2仿真对比验证了该算法的有效性。     

基于排队分析的端到端路径可用带宽的测量

端到端路径可用带宽是衡量网络性能的重要指标.目前,大多数对可用带宽测量的研究都集中在自拥塞方法上,但自拥塞方法会严重影响路径上的原有流量,因此,提出了一种基于模型的方法,将Internet视为一个具有单一服务单元且服务两种流量(探测流量和背景流量)的排队系统,通过分析探测流量离开排队系统的过程,在路径的负载与探测流量离去间隔的变异系数之间建立了对应关系,并在此基础上获得可用带宽值.与自拥塞方法相比,不会造成路径拥塞且具有较好的准确性.     

一种基于M/D/1排队模型的可用带宽测量算法

由于液体流模型不能反映实际背景流的突发性及包长分布,基于液体流模型的可用带宽测量技术在突发背景流及多跳链路下测量精度较低.因此,提出了一种基于M/D/1排队模型的高精度可用带宽测量算法FPU(five-packet-unit for available bandwidth measurement).该算法采用五包结构构...     

一种自适应的高精度可用带宽测量算法

针对现有可用带宽测量技术在突发背景流及多跳链路下测量精度较低的问题,提出了一种自适应的高精度可用带宽测量算法FPU-ABM(Five-Packet-Unit for Available Bandwidth Measurement);该算法采用五包结构构成探测单元,结合TTL值设置,分别测量瓶颈链路前后的探测包间隔,提高了在多跳链路下带宽测量精度;算法根据反馈包的间隔自适应地调整探测速率,加快了测量速度且减小了探测流对网络的入侵度,增强了算法的适应性;仿真表明,在多跳链路下TFP-ABM算法的测量精度可达到10%以内,相比现有算法,TFP-ABM响应速度快、测量精度高、适应性好。     

一种测量任意链路可用带宽的方法

可用带宽测量对于网络行为分析、网络服务质量(quality of service,简称QoS)的验证等有很重要的作用.现有可用带宽测量工作主要集中在端到端路径可用带宽测量,仅提供路径上承压链路(tight link)的信息,而不能提供其他关键链路的信息.为此,提出一种新颖的链路可用带宽测量算法LinkPPQ(trains of pairs of packet-quartets used to measure available bandwidth of arbitrary links),它采用由四探测分组结构对构成的探测序列,能够测量网络中任意链路的可用带宽,并跟踪该链路上背景流的变化.在仿真环境和实际网络环境下研究了LinkPPQ 的性能.仿真结果表明,在几种不同背景流场景下,对于具有单狭窄链路的路径和具有多狭窄链路的路径,LinkPPQ 都能够对各个链路的可用带宽进行有效的测量.绝大多数情况下测量误差小于30%,且具有较好的测量平稳性.实验网的实验结果也表明,LinkPPQ 可以准确测量以下几种情况下的链路的可用带宽:a) 从容量为10Mbps 的链路准确地测量一条100Mbps 链路的可用带宽;b) 准确测量容量10 倍于紧邻其后狭窄链路的容量的链路的可用带宽;c) 准确测量具有多狭窄链路的路径上各狭窄链路的可用带宽.     

一种紧链路定位和可用带宽测量的方法

可用带宽与紧链路是两个重要的QoS指标,在拥塞控制、流媒体应用、QoS验证、服务器选择等领域具有重要意义。文章详细描述了Pathtrait,一种可以准确测量可用带宽和定位紧链路的方法。Pathtrait基于一种全新的探针结构,以捕获探针队列在路径某跳的输入速率和输出速率,由此定位紧链路、估算紧链路处的链路可用带宽。该文在NS2仿真环境中验证了Pathtrait的准确性。     

网络主动带宽测量算法设计

本文基于Cruz流量模型.通过主动检测单向时延连续上升的概率.推断探测速率与端到端可用带宽之间的关系,提出一种网络可用带宽主动测量算法PathPCQ.NS2仿真显示,PathPCQ算法测量精度和效率都优于现有的带宽测量工具Pathload.     

SLDRT: A measurement technique for available bandwidth on multi-hop path with bursty cross traffic

End-to-end available bandwidth is of great importance as a metric that characterizes the network’s dynamic transmitting capability. Most estimation methodologies infer available bandwidth from the relationship between the input inter-packet gaps and those of the output. This paper analyzes the challenges brought by extending the measurement environment to the multi-hop path with bursty cross-traffic. Based on the analysis, a novel probing technique, self-loading decreasing rate train (SLDRT), is proposed. SLDRT measures the available bandwidth by using a single decreasing rate packet train. The special train can efficiently avoid bias caused by multiple sampling. Performance analysis via NS-2 simulations and PlanetLab experiments verify the effectiveness of our method under multi-hop path with the bursty cross traffic environment, and also show that SLDRT estimates available bandwidth more quickly, accurately, and with less measurement overhead than other existing techniques such as pathload and pathChirp.     

Granular model of packet pair separation in Poissonian traffic

We introduce a theoretical model of packet pair separation based on a transient solution of the Takács integro-differential equation. We show that in addition to the parameters of the fluid approximation (physical bandwidth and the average cross traffic rate) a new parameter characterizing the granularity of the cross traffic is necessary. These three parameters determine the dynamics of the queue in the diffusive approximation and all important distributions and averages of the packet separation even in multi-hop scenarios (assuming independent cross traffic on different hops). The model describes correctly the data collected in simulations, laboratory and Internet experiments. The adjustable model parameters are the physical bandwidth, the available bandwidth and the weighted average of the packet size of the cross traffic. We show that an implementation of the theoretical results can be used to estimate such parameters in packet chirp type measurements and can be a good candidate for improved available bandwidth estimation.     

Available bandwidth estimation for the network paths with multiple tight links and bursty traffic

Available bandwidth (ABW) estimation is useful for various applications such as network management, traffic engineering, and rate-based multimedia streaming. Most of the ABW estimation methods are based on the fluid cross-traffic model. Inevitably, their estimation accuracy is limited in the network environments with bursty cross-traffic. In this paper, we apply packet trains (a series of probing packets) and a modified Ping to probe the ABW of a network path. Our proposed probing method can identify several tight links along a path and can infer their individual ABWs. The ABW estimation algorithm developed in this study, GNAPP, is also based on the fluid traffic model, but it can effectively filter out probing noise incurred in networks that carry bursty traffic. The algorithm employs not only the gaps of any two consecutive probing packets but also those of nonadjacent probing packets for ABW estimation. Thus, the number of samples for ABW estimation increases significantly without resorting to sending more probing packets and the estimation efficiency and accuracy are improved. In addition, two-stage filtering and moving averages are used in GNAPP for reducing estimation errors. Numerical results demonstrate that the estimation scheme based on GNAPP can achieve good accuracy even when the traffic is bursty and there are multiple tight links on the path being observed. Thus, it outperforms other well-known ABW estimation tools.     

Analysis of minimal backlogging-based available bandwidth estimation mechanism

This paper analyzes the minimal backlogging-based available bandwidth estimation mechanism to strengthen the theory behind the mechanism. The minimal backlogging method estimates the available bandwidth using the statistic of the probing traffic service rate. We show that the statistic of the probing traffic service rate is a consistent estimator of the available bandwidth for a G/G/1 queueing system under minimal backlogging condition to support the minimal backlogging method theoretically. In order to emulate the minimal backlogging method in a real multi-hop network, we detect the minimal backlogging condition or closeness of the probing rate to the available bandwidth based on the busy period length, and change the probing rate adaptively to maintain the minimal backlogging condition. We explain that the minimal backlogging condition or available bandwidth might be detected more accurately by the busy period of probing packets than by the gap response curve or rate response curve, and enhance the minimal backlogging method further by introducing a new initial probing rate estimation mechanism. A reasonable range of available bandwidth for a short time interval can be obtained using the mean and variance of the estimated available bandwidth, since the proposed mechanism can estimate the available bandwidth quickly and track it adaptively. The proposed mechanism is implemented in a Linux environment. The performance of our scheme is compared to those of conventional available bandwidth estimation mechanisms through experiments on a test-bed with single-hop or multiple-hop topologies.     

基于测量的QoS参数估计及其应用

提出了一种基于测量的QoS参数估计方法,该方法使得用户无须事先为业务源建立相应的业务模型并向网络提交其业务模型参数,而是通过对业务流的统计特性进行实时测量来动态估计相应的QoS参数,从而克服了基于模型QoS参数估计方法所固有的缺陷,便于网络进行连接允许控制和带宽的动态分配.     

基于序贯模式挖掘的宏观网络流量异常检测

基于序贯频繁模式挖掘,提出并实现了一种宏观网络流量异常检测的方法。定义了一个新的频繁模式和相对应的异常度概念。对863-917网络安全监测平台提供的全国流量数据进行了实验,得出对应于“橙色八月”的2006年8月上旬流量严重异常的结论。通过与相关的其他传统算法进行对比,如使用绝对流量的算法和简单使用不同小时流量排名的算法,进一步说明序贯频繁模式对网络流量分析的实用性。     

包对探测统计模型与测量精度分析*

包对模型(PGM)是探测可用带宽的主要方法。该方法存在以下问题,影响其推广应用：模型没有精确的数学模型描述,原有模型假设流量包长看做无限小,与实际网络情况不符合;没有定量方法计算探测精度、样本容量,给测量带来不便;没有分析互联网数据包突发性对测量带来的影响。为解决以上问题,通过对包对模型进行数学建模的方法,证明了模型正确性;定量分析了测量精度;确定了样本数计算公式;分析了数据包突发性对探测造成的影响;最后对以上分析进行了仿真实验验证,提高了可用带宽测试技术的精度和可信度。     

Access network selection based on available bandwidth estimation for heterogeneous networks

With the new 5G trend, the amount of heterogeneous networks (HetNets) has increased exponentially. Cooperation between the most commonly used HetNets such as: WiFi and Long Term Evolution (LTE) is required to ensure a balanced traffic load which benefits the end user with maximum throughput and high quality of service. A balanced traffic problem with WiFi- LTE heterogeneous wireless networks is selecting which network to use, LTE or WiFi, if both are available. In other words, a node would have to send/receive traffic using either LTE or WiFi. We address this issue and propose both a WiFi available bandwidth estimation technique called “Available Bandwidth with Error Probability (ABEP)” and a traffic steering strategy to improve the performance of WiFi-LTE wireless networks. Our approach provides a better estimation of available bandwidth in WiFi with respect to relevant bandwidth estimation techniques. The bandwidth utilization in a WiFi Network is obtained at an initial stage of the traffic steering strategy. The steering of traffic is then triggered depending on events and the network conditions. Different from other approaches, our proposed traffic steering algorithm considers both a minimum bandwidth and a minimum SNR threshold to connect to WiFi, which are necessary to have an efficient transmission. One of the benefits of our approach regards reducing the use of the LTE network and its corresponding monetary charges.     

Effective bandwidth estimation and testing for Markov sources

This work addresses the resource sharing problem in broadband communication networks that can guarantee some quality of service (QoS), and develops some results about data source and traffic modelling, especially in aspects of model testing and parameter estimation. The multiplexing of variable bit rate (VBR) sources poses a mathematical and statistical problem: the estimation of the resource requirements of a source or set of sources. The estimation method shall be simple enough to be practically implemented in the connection acceptance control (CAC) function.

In this paper, the VBR video sources are taken as a typical case of variable rate, with real-time constraints. This association of requirements makes the case especially interesting. A Markov model is assumed for the VBR sources. The validity of such models is under research; they seem to be appropriate at least in certain time scales. The model is tested against real video traces. In order to estimate the resource allocation or “channel occupation” of each source, the concept of equivalent bandwidth proposed by Kelly [Notes on effective bandwidth, in: F.P. Kelly, S. Zachary, I.B. Ziedins (Eds.), Stochastic Networks: Theory and Applications, Oxford University Press, Oxford, 1996, pp. 141] is used; it is based on a consistent mathematical theory, and has proven to be robust and useful for technical applications.

A calculation of the equivalent bandwidth of a Markov source, given its parameters, can be found in the literature [IEEE ACM Trans. Networking 1 (4) (1993) 424]. But in fact, one can only estimate model and parameters. In this work, an estimation of the equivalent bandwidth is given, which can be obtained from real data. The convergence and the consistency of the estimation are studied, and practical bounds are found. Illustrative calculations are performed from real video traces that were obtained using a software MPEG coder, developed by the authors. The mathematical and statistical results are valid for whatever phenomenon that can be modelled as a Markov process.